repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
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speechbrain | speechbrain-main/speechbrain/nnet/complex_networks/c_RNN.py | """Library implementing complex-valued recurrent neural networks.
Authors
* Titouan Parcollet 2020
"""
import torch
import logging
from speechbrain.nnet.complex_networks.c_linear import CLinear
from speechbrain.nnet.complex_networks.c_normalization import (
CBatchNorm,
CLayerNorm,
)
logger = logging.getLogg... | 38,455 | 31.153846 | 97 | py |
speechbrain | speechbrain-main/speechbrain/nnet/complex_networks/c_linear.py | """Library implementing complex-valued linear transformation.
Authors
* Titouan Parcollet 2020
"""
import torch
import logging
from speechbrain.nnet.complex_networks.c_ops import (
affect_init,
complex_init,
unitary_init,
complex_linear_op,
check_complex_input,
)
logger = logging.getLogger(__nam... | 4,020 | 32.508333 | 97 | py |
speechbrain | speechbrain-main/speechbrain/nnet/transducer/transducer_joint.py | """Library implementing transducer_joint.
Author
Abdelwahab HEBA 2020
"""
import torch
import logging
import torch.nn as nn
logger = logging.getLogger(__name__)
class Transducer_joint(nn.Module):
"""Computes joint tensor between Transcription network (TN) & Prediction network (PN)
Arguments
------... | 3,106 | 31.364583 | 89 | py |
speechbrain | speechbrain-main/speechbrain/nnet/transducer/__init__.py | """Package containing transducer neural networks
"""
| 53 | 17 | 48 | py |
speechbrain | speechbrain-main/speechbrain/nnet/quaternion_networks/q_RNN.py | """Library implementing quaternion-valued recurrent neural networks.
Authors
* Titouan Parcollet 2020
"""
import torch
import logging
from speechbrain.nnet.quaternion_networks.q_linear import QLinear
from speechbrain.nnet.quaternion_networks.q_normalization import QBatchNorm
from torch import Tensor
from typing impo... | 40,503 | 32.06449 | 94 | py |
speechbrain | speechbrain-main/speechbrain/nnet/quaternion_networks/q_CNN.py | """Library implementing quaternion-valued convolutional neural networks.
Authors
* Titouan Parcollet 2020
"""
import torch
import torch.nn as nn
import logging
import torch.nn.functional as F
from speechbrain.nnet.CNN import get_padding_elem
from speechbrain.nnet.quaternion_networks.q_ops import (
unitary_init,
... | 20,523 | 32.980132 | 94 | py |
speechbrain | speechbrain-main/speechbrain/nnet/quaternion_networks/q_ops.py | """This library implements different operations needed by quaternion-
valued architectures.
This work is inspired by:
"Quaternion neural networks" - Parcollet T.
"Quaternion recurrent neural networks" - Parcollet T. et al.
"Quaternion convolutional neural networks for end-to-end automatic speech
recognition" - Parcolle... | 28,142 | 33.362637 | 80 | py |
speechbrain | speechbrain-main/speechbrain/nnet/quaternion_networks/q_normalization.py | """Library implementing quaternion-valued normalization.
Authors
* Titouan Parcollet 2020
"""
import torch
from torch.nn import Parameter
class QBatchNorm(torch.nn.Module):
"""This class implements the simplest form of a quaternion batchnorm as
described in : "Quaternion Convolutional Neural Network for
... | 5,396 | 31.908537 | 89 | py |
speechbrain | speechbrain-main/speechbrain/nnet/quaternion_networks/__init__.py | """Package containing quaternion neural networks
"""
| 53 | 17 | 48 | py |
speechbrain | speechbrain-main/speechbrain/nnet/quaternion_networks/q_linear.py | """Library implementing quaternion-valued linear transformation.
Authors
* Titouan Parcollet 2020
"""
import torch
import logging
from speechbrain.nnet.quaternion_networks.q_ops import (
affect_init,
unitary_init,
quaternion_init,
quaternion_linear_op,
check_quaternion_input,
quaternion_linea... | 7,965 | 34.721973 | 94 | py |
speechbrain | speechbrain-main/speechbrain/nnet/loss/transducer_loss.py | """
Transducer loss implementation (depends on numba)
Authors
* Abdelwahab Heba 2020
"""
import torch
from torch.autograd import Function
from torch.nn import Module
try:
from numba import cuda
except ImportError:
err_msg = "The optional dependency Numba is needed to use this module\n"
err_msg += "Canno... | 14,074 | 38.985795 | 167 | py |
speechbrain | speechbrain-main/speechbrain/nnet/loss/stoi_loss.py | """Library for computing STOI computation.
Reference: "End-to-End Waveform Utterance Enhancement for Direct Evaluation
Metrics Optimization by Fully Convolutional Neural Networks", TASLP, 2018
Authors:
Szu-Wei, Fu 2020
"""
import torch
import torchaudio
import numpy as np
from speechbrain.utils.torch_audio_backen... | 6,489 | 28.770642 | 76 | py |
speechbrain | speechbrain-main/speechbrain/nnet/loss/guidedattn_loss.py | """The Guided Attention Loss implementation
This loss can be used to speed up the training of
models in which the correspondence between inputs and
outputs is roughly linear, and the attention alignments
are expected to be approximately diagonal, such as Grapheme-to-Phoneme
and Text-to-Speech
Authors
* Artem Ploujnik... | 5,760 | 31.184358 | 87 | py |
speechbrain | speechbrain-main/speechbrain/nnet/loss/__init__.py | """Package containing specific losses (transducer, stoi ...)
"""
| 65 | 21 | 60 | py |
speechbrain | speechbrain-main/speechbrain/nnet/loss/si_snr_loss.py | """
# Authors:
* Szu-Wei, Fu 2021
* Mirco Ravanelli 2020
* Samuele Cornell 2020
* Hwidong Na 2020
* Yan Gao 2020
* Titouan Parcollet 2020
"""
import torch
import numpy as np
smallVal = np.finfo("float").eps # To avoid divide by zero
def si_snr_loss(y_pred_batch, y_true_batch, lens, reduction="mean"):
"""... | 1,912 | 27.132353 | 78 | py |
speechbrain | speechbrain-main/speechbrain/pretrained/training.py | """
Training utilities for pretrained models
Authors
* Artem Ploujnikov 2021
"""
import os
import logging
import shutil
logger = logging.getLogger(__name__)
def save_for_pretrained(
hparams,
min_key=None,
max_key=None,
ckpt_predicate=None,
pretrainer_key="pretrainer",
checkpointer_key="check... | 2,987 | 32.2 | 82 | py |
speechbrain | speechbrain-main/speechbrain/pretrained/interfaces.py | """Defines interfaces for simple inference with pretrained models
Authors:
* Aku Rouhe 2021
* Peter Plantinga 2021
* Loren Lugosch 2020
* Mirco Ravanelli 2020
* Titouan Parcollet 2021
* Abdel Heba 2021
* Andreas Nautsch 2022
* Pooneh Mousavi 20023
"""
import logging
import hashlib
import sys
import speechbrain... | 107,365 | 34.812542 | 122 | py |
speechbrain | speechbrain-main/speechbrain/pretrained/fetching.py | """Downloads or otherwise fetches pretrained models
Authors:
* Aku Rouhe 2021
* Samuele Cornell 2021
"""
import urllib.request
import urllib.error
import pathlib
import logging
import huggingface_hub
from requests.exceptions import HTTPError
logger = logging.getLogger(__name__)
def _missing_ok_unlink(path):
#... | 4,921 | 34.927007 | 101 | py |
speechbrain | speechbrain-main/speechbrain/pretrained/__init__.py | """Pretrained models"""
from .interfaces import * # noqa
| 59 | 14 | 33 | py |
speechbrain | speechbrain-main/speechbrain/dataio/legacy.py | """SpeechBrain Extended CSV Compatibility."""
from speechbrain.dataio.dataset import DynamicItemDataset
import collections
import csv
import pickle
import logging
import torch
import torchaudio
import re
logger = logging.getLogger(__name__)
TORCHAUDIO_FORMATS = ["wav", "flac", "aac", "ogg", "flac", "mp3"]
ITEM_POSTF... | 10,629 | 32.533123 | 79 | py |
speechbrain | speechbrain-main/speechbrain/dataio/dataio.py | """
Data reading and writing.
Authors
* Mirco Ravanelli 2020
* Aku Rouhe 2020
* Ju-Chieh Chou 2020
* Samuele Cornell 2020
* Abdel HEBA 2020
* Gaelle Laperriere 2021
* Sahar Ghannay 2021
* Sylvain de Langen 2022
"""
import os
import torch
import logging
import numpy as np
import pickle
import hashlib
import csv... | 34,200 | 28.560069 | 187 | py |
speechbrain | speechbrain-main/speechbrain/dataio/sampler.py | """PyTorch compatible samplers.
These determine the order of iteration through a dataset.
Authors:
* Aku Rouhe 2020
* Samuele Cornell 2020
* Ralf Leibold 2020
* Artem Ploujnikov 2021
* Andreas Nautsch 2021
"""
import torch
import logging
from operator import itemgetter
from torch.utils.data import (
Ran... | 32,036 | 38.212974 | 132 | py |
speechbrain | speechbrain-main/speechbrain/dataio/batch.py | """Batch collation
Authors
* Aku Rouhe 2020
"""
import collections
import torch
from speechbrain.utils.data_utils import mod_default_collate
from speechbrain.utils.data_utils import recursive_to
from speechbrain.utils.data_utils import batch_pad_right
from torch.utils.data._utils.collate import default_convert
from ... | 9,022 | 32.172794 | 91 | py |
speechbrain | speechbrain-main/speechbrain/dataio/dataloader.py | """PyTorch compatible DataLoaders
Essentially we extend PyTorch DataLoader by adding the ability to save the
data loading state, so that a checkpoint may be saved in the middle of an
epoch.
Example
-------
>>> import torch
>>> from speechbrain.utils.checkpoints import Checkpointer
>>> # An example "dataset" and its l... | 13,097 | 36.637931 | 86 | py |
speechbrain | speechbrain-main/speechbrain/dataio/encoder.py | """Encoding categorical data as integers
Authors
* Samuele Cornell 2020
* Aku Rouhe 2020
"""
import ast
import torch
import collections
import itertools
import logging
import speechbrain as sb
from speechbrain.utils.checkpoints import (
mark_as_saver,
mark_as_loader,
register_checkpoint_hooks,
)
logge... | 39,147 | 34.718978 | 93 | py |
speechbrain | speechbrain-main/speechbrain/dataio/dataset.py | """Dataset examples for loading individual data points
Authors
* Aku Rouhe 2020
* Samuele Cornell 2020
"""
import copy
import contextlib
from types import MethodType
from torch.utils.data import Dataset
from speechbrain.utils.data_pipeline import DataPipeline
from speechbrain.dataio.dataio import load_data_json, ... | 15,593 | 36.30622 | 87 | py |
speechbrain | speechbrain-main/speechbrain/dataio/iterators.py | """Webdataset compatible iterators
Authors:
* Aku Rouhe 2021
"""
import bisect
import random
from dataclasses import dataclass, field
from functools import partial
from typing import Any
from speechbrain.dataio.batch import PaddedBatch
@dataclass(order=True)
class LengthItem:
""" Data class for lenghts"""
... | 8,487 | 37.234234 | 84 | py |
speechbrain | speechbrain-main/speechbrain/dataio/__init__.py | """Data loading and dataset preprocessing
"""
import os
__all__ = []
for filename in os.listdir(os.path.dirname(__file__)):
filename = os.path.basename(filename)
if filename.endswith(".py") and not filename.startswith("__"):
__all__.append(filename[:-3])
from . import * # noqa
| 297 | 23.833333 | 66 | py |
speechbrain | speechbrain-main/speechbrain/dataio/preprocess.py | """Preprocessors for audio"""
import torch
import functools
from speechbrain.processing.speech_augmentation import Resample
class AudioNormalizer:
"""Normalizes audio into a standard format
Arguments
---------
sample_rate : int
The sampling rate to which the incoming signals should be convert... | 2,293 | 32.735294 | 87 | py |
speechbrain | speechbrain-main/speechbrain/dataio/wer.py | """WER print functions.
The functions here are used to print the computed statistics
with human-readable formatting.
They have a file argument, but you can also just use
contextlib.redirect_stdout, which may give a nicer syntax.
Authors
* Aku Rouhe 2020
"""
import sys
from speechbrain.utils import edit_distance
de... | 6,315 | 30.89899 | 138 | py |
speechbrain | speechbrain-main/speechbrain/alignment/ctc_segmentation.py | #!/usr/bin/env python3
# 2021, Technische Universität München, Ludwig Kürzinger
"""Perform CTC segmentation to align utterances within audio files.
This uses the ctc-segmentation Python package.
Install it with pip or see the installing instructions in
https://github.com/lumaku/ctc-segmentation
"""
import logging
fro... | 26,318 | 38.577444 | 84 | py |
speechbrain | speechbrain-main/speechbrain/alignment/__init__.py | """Tools for aligning transcripts and speech signals
"""
| 57 | 18.333333 | 52 | py |
speechbrain | speechbrain-main/speechbrain/alignment/aligner.py | """
Alignment code
Authors
* Elena Rastorgueva 2020
* Loren Lugosch 2020
"""
import torch
import random
from speechbrain.utils.checkpoints import register_checkpoint_hooks
from speechbrain.utils.checkpoints import mark_as_saver
from speechbrain.utils.checkpoints import mark_as_loader
from speechbrain.utils.data_util... | 52,837 | 34.944218 | 96 | py |
speechbrain | speechbrain-main/speechbrain/lm/arpa.py | r"""
Tools for working with ARPA format N-gram models
Expects the ARPA format to have:
- a \data\ header
- counts of ngrams in the order that they are later listed
- line breaks between \data\ and \n-grams: sections
- \end\
E.G.
```
\data\
ngram 1=2
ngram 2=1
\1-grams:
-1.0000 Hello -0.23
... | 7,508 | 31.647826 | 80 | py |
speechbrain | speechbrain-main/speechbrain/lm/counting.py | """
N-gram counting, discounting, interpolation, and backoff
Authors
* Aku Rouhe 2020
"""
import itertools
# The following functions are essentially copying the NLTK ngram counting
# pipeline with minor differences. Written from scratch, but with enough
# inspiration that I feel I want to mention the inspiration so... | 4,500 | 26.613497 | 79 | py |
speechbrain | speechbrain-main/speechbrain/lm/ngram.py | """
N-gram language model query interface
Authors
* Aku Rouhe 2020
"""
import collections
NEGINFINITY = float("-inf")
class BackoffNgramLM:
"""
Query interface for backoff N-gram language models
The ngrams format is best explained by an example query: P( world | <s>,
hello ), i.e. trigram model, p... | 6,939 | 33.527363 | 79 | py |
speechbrain | speechbrain-main/speechbrain/lm/__init__.py | """ Package defining language models
"""
| 41 | 13 | 36 | py |
speechbrain | speechbrain-main/speechbrain/utils/epoch_loop.py | """Implements a checkpointable epoch counter (loop), optionally integrating early stopping.
Authors
* Aku Rouhe 2020
* Davide Borra 2021
"""
from .checkpoints import register_checkpoint_hooks
from .checkpoints import mark_as_saver
from .checkpoints import mark_as_loader
import logging
logger = logging.getLogger(__n... | 4,557 | 33.014925 | 118 | py |
speechbrain | speechbrain-main/speechbrain/utils/edit_distance.py | """Edit distance and WER computation.
Authors
* Aku Rouhe 2020
* Salima Mdhaffar 2021
"""
import collections
EDIT_SYMBOLS = {
"eq": "=", # when tokens are equal
"ins": "I",
"del": "D",
"sub": "S",
}
# NOTE: There is a danger in using mutables as default arguments, as they are
# only initialized ... | 25,986 | 33.788487 | 80 | py |
speechbrain | speechbrain-main/speechbrain/utils/checkpoints.py | """This module implements a checkpoint saver and loader.
A checkpoint in an experiment usually needs to save the state of many different
things: the model parameters, optimizer parameters, what epoch is this, etc.
The save format for a checkpoint is a directory, where each of these separate
saveable things gets its ow... | 45,420 | 36.850833 | 88 | py |
speechbrain | speechbrain-main/speechbrain/utils/profiling.py | """Polymorphic decorators to handle PyTorch profiling and benchmarking.
Author:
* Andreas Nautsch 2022
"""
import numpy as np
from copy import deepcopy
from torch import profiler
from functools import wraps
from typing import Any, Callable, Iterable, Optional
# from typing import List
# from itertools import chai... | 25,566 | 36.653903 | 120 | py |
speechbrain | speechbrain-main/speechbrain/utils/data_utils.py | """This library gathers utilities for data io operation.
Authors
* Mirco Ravanelli 2020
* Aku Rouhe 2020
* Samuele Cornell 2020
"""
import os
import re
import csv
import shutil
import urllib.request
import collections.abc
import torch
import tqdm
import pathlib
import speechbrain as sb
def undo_padding(batch, le... | 17,403 | 28.90378 | 123 | py |
speechbrain | speechbrain-main/speechbrain/utils/callchains.py | """Chaining together callables, if some require relative lengths"""
import inspect
def lengths_arg_exists(func):
"""Returns True if func takes ``lengths`` keyword argument.
Arguments
---------
func : callable
The function, method, or other callable to search for the lengths arg.
"""
s... | 2,361 | 27.804878 | 78 | py |
speechbrain | speechbrain-main/speechbrain/utils/logger.py | """Managing the logger, utilities
Author
* Fang-Pen Lin 2012 https://fangpenlin.com/posts/2012/08/26/good-logging-practice-in-python/
* Peter Plantinga 2020
* Aku Rouhe 2020
"""
import sys
import os
import yaml
import tqdm
import logging
import logging.config
import math
import torch
from speechbrain.utils.data_ut... | 5,525 | 27.050761 | 93 | py |
speechbrain | speechbrain-main/speechbrain/utils/hpopt.py | """Utilities for hyperparameter optimization.
This wrapper has an optional dependency on
Oríon
https://orion.readthedocs.io/en/stable/
https://github.com/Epistimio/orion
Authors
* Artem Ploujnikov 2021
"""
import importlib
import logging
import json
import os
import speechbrain as sb
import sys
from datetime import... | 13,211 | 28.756757 | 93 | py |
speechbrain | speechbrain-main/speechbrain/utils/_workarounds.py | """This module implements some workarounds for dependencies
Authors
* Aku Rouhe 2022
"""
import torch
import weakref
import warnings
WEAKREF_MARKER = "WEAKREF"
def _cycliclrsaver(obj, path):
state_dict = obj.state_dict()
if state_dict.get("_scale_fn_ref") is not None:
state_dict["_scale_fn_ref"] = ... | 1,188 | 33.970588 | 95 | py |
speechbrain | speechbrain-main/speechbrain/utils/metric_stats.py | """The ``metric_stats`` module provides an abstract class for storing
statistics produced over the course of an experiment and summarizing them.
Authors:
* Peter Plantinga 2020
* Mirco Ravanelli 2020
* Gaelle Laperriere 2021
* Sahar Ghannay 2021
"""
import torch
from joblib import Parallel, delayed
from speechbra... | 31,718 | 33.069817 | 109 | py |
speechbrain | speechbrain-main/speechbrain/utils/hparams.py | """Utilities for hparams files
Authors
* Artem Ploujnikov 2021
"""
def choice(value, choices, default=None):
"""
The equivalent of a "switch statement" for hparams files. The typical use case
is where different options/modules are available, and a top-level flag decides
which one to use
Argumen... | 921 | 26.117647 | 82 | py |
speechbrain | speechbrain-main/speechbrain/utils/DER.py | """Calculates Diarization Error Rate (DER) which is the sum of Missed Speaker (MS),
False Alarm (FA), and Speaker Error Rate (SER) using md-eval-22.pl from NIST RT Evaluation.
Authors
* Neville Ryant 2018
* Nauman Dawalatabad 2020
Credits
This code is adapted from https://github.com/nryant/dscore
"""
import os
im... | 4,464 | 28.183007 | 104 | py |
speechbrain | speechbrain-main/speechbrain/utils/superpowers.py | """Superpowers which should be sparingly used.
This library contains functions for importing python files and
for running shell commands. Remember, with great power comes great
responsibility.
Authors
* Mirco Ravanelli 2020
* Aku Rouhe 2021
"""
import logging
import subprocess
import importlib
import pathlib
logg... | 1,962 | 21.306818 | 85 | py |
speechbrain | speechbrain-main/speechbrain/utils/parameter_transfer.py | """Convenience functions for the simplest parameter transfer cases.
Use `speechbrain.utils.checkpoints.Checkpointer` to find a checkpoint
and the path to the parameter file.
Authors
* Aku Rouhe 2020
"""
import logging
import pathlib
from speechbrain.pretrained.fetching import fetch
from speechbrain.utils.checkpoint... | 9,651 | 32.985915 | 83 | py |
speechbrain | speechbrain-main/speechbrain/utils/distributed.py | """Guard for running certain operations on main process only
Authors:
* Abdel Heba 2020
* Aku Rouhe 2020
"""
import os
import torch
import logging
logger = logging.getLogger(__name__)
def run_on_main(
func,
args=None,
kwargs=None,
post_func=None,
post_args=None,
post_kwargs=None,
run_p... | 6,388 | 33.349462 | 80 | py |
speechbrain | speechbrain-main/speechbrain/utils/text_to_sequence.py | """ from https://github.com/keithito/tacotron """
# *****************************************************************************
# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the foll... | 8,219 | 24.768025 | 147 | py |
speechbrain | speechbrain-main/speechbrain/utils/bleu.py | """Library for computing the BLEU score
Authors
* Mirco Ravanelli 2021
"""
from speechbrain.utils.metric_stats import MetricStats
def merge_words(sequences):
"""Merge successive words into phrase, putting space between each word
Arguments
---------
sequences : list
Each item contains a lis... | 3,943 | 28 | 112 | py |
speechbrain | speechbrain-main/speechbrain/utils/data_pipeline.py | """A pipeline for data transformations.
Example
-------
>>> from hyperpyyaml import load_hyperpyyaml
>>> yamlstring = '''
... pipeline: !new:speechbrain.utils.data_pipeline.DataPipeline
... static_data_keys: [a, b]
... dynamic_items:
... - func: !name:operator.add
... takes: ["a", "b"]
..... | 18,934 | 35.273946 | 80 | py |
speechbrain | speechbrain-main/speechbrain/utils/__init__.py | """ Package containing various tools (accuracy, checkpoints ...)
"""
import os
__all__ = []
for filename in os.listdir(os.path.dirname(__file__)):
filename = os.path.basename(filename)
if filename.endswith(".py") and not filename.startswith("__"):
__all__.append(filename[:-3])
from . import * # noqa
| 320 | 25.75 | 66 | py |
speechbrain | speechbrain-main/speechbrain/utils/Accuracy.py | """Calculate accuracy.
Authors
* Jianyuan Zhong 2020
"""
import torch
from speechbrain.dataio.dataio import length_to_mask
def Accuracy(log_probabilities, targets, length=None):
"""Calculates the accuracy for predicted log probabilities and targets in a batch.
Arguments
----------
log_probabilities ... | 2,584 | 29.05814 | 99 | py |
speechbrain | speechbrain-main/speechbrain/utils/torch_audio_backend.py | """Library for checking the torchaudio backend.
Authors
* Mirco Ravanelli 2021
"""
import platform
import logging
import torchaudio
logger = logging.getLogger(__name__)
def check_torchaudio_backend():
"""Checks the torchaudio backend and sets it to soundfile if
windows is detected.
"""
current_syst... | 573 | 23.956522 | 112 | py |
speechbrain | speechbrain-main/speechbrain/utils/depgraph.py | """A dependency graph for finding evaluation order.
Example
-------
>>> # The basic use case is that you have a bunch of keys
>>> # and some of them depend on each other:
>>> database = []
>>> functions = {'read': {'func': lambda: (0,1,2),
... 'needs': []},
... 'process': {'func': la... | 9,678 | 33.942238 | 81 | py |
speechbrain | speechbrain-main/speechbrain/utils/train_logger.py | """Loggers for experiment monitoring.
Authors
* Peter Plantinga 2020
"""
import logging
import ruamel.yaml
import torch
import os
logger = logging.getLogger(__name__)
class TrainLogger:
"""Abstract class defining an interface for training loggers."""
def log_stats(
self,
stats_meta,
... | 13,898 | 30.445701 | 168 | py |
speechbrain | speechbrain-main/speechbrain/processing/NMF.py | """Non-negative matrix factorization
Authors
* Cem Subakan
"""
import torch
from speechbrain.processing.features import spectral_magnitude
import speechbrain.processing.features as spf
def spectral_phase(stft, power=2, log=False):
"""Returns the phase of a complex spectrogram.
Arguments
---------
s... | 5,770 | 29.373684 | 103 | py |
speechbrain | speechbrain-main/speechbrain/processing/features.py | """Low-level feature pipeline components
This library gathers functions that compute popular speech features over
batches of data. All the classes are of type nn.Module. This gives the
possibility to have end-to-end differentiability and to backpropagate the
gradient through them. Our functions are a modified versio... | 39,570 | 31.435246 | 81 | py |
speechbrain | speechbrain-main/speechbrain/processing/speech_augmentation.py | """Classes for mutating speech data for data augmentation.
This module provides classes that produce realistic distortions of speech
data for the purpose of training speech processing models. The list of
distortions includes adding noise, adding reverberation, changing speed,
and more. All the classes are of type `tor... | 44,293 | 34.982128 | 81 | py |
speechbrain | speechbrain-main/speechbrain/processing/PLDA_LDA.py | """A popular speaker recognition/diarization model (LDA and PLDA).
Authors
* Anthony Larcher 2020
* Nauman Dawalatabad 2020
Relevant Papers
- This implementation of PLDA is based on the following papers.
- PLDA model Training
* Ye Jiang et. al, "PLDA Modeling in I-Vector and Supervector Space for Speaker Ver... | 34,751 | 33.238424 | 132 | py |
speechbrain | speechbrain-main/speechbrain/processing/signal_processing.py | """
Low level signal processing utilities
Authors
* Peter Plantinga 2020
* Francois Grondin 2020
* William Aris 2020
* Samuele Cornell 2020
* Sarthak Yadav 2022
"""
import torch
import math
from packaging import version
def compute_amplitude(waveforms, lengths=None, amp_type="avg", scale="linear"):
"""Compu... | 20,913 | 32.677939 | 123 | py |
speechbrain | speechbrain-main/speechbrain/processing/diarization.py | """
This script contains basic functions used for speaker diarization.
This script has an optional dependency on open source scikit-learn (sklearn) library.
A few scikit-learn functions are modified in this script as per requirement.
Reference
---------
This code is written using the following:
- Von Luxburg, U. A tu... | 36,922 | 29.743547 | 116 | py |
speechbrain | speechbrain-main/speechbrain/processing/multi_mic.py | """Multi-microphone components.
This library contains functions for multi-microphone signal processing.
Example
-------
>>> import torch
>>>
>>> from speechbrain.dataio.dataio import read_audio
>>> from speechbrain.processing.features import STFT, ISTFT
>>> from speechbrain.processing.multi_mic import Covariance
>>> ... | 53,438 | 33.836375 | 120 | py |
speechbrain | speechbrain-main/speechbrain/processing/decomposition.py | """
Generalized Eigenvalue Decomposition.
This library contains different methods to adjust the format of
complex Hermitian matrices and find their eigenvectors and
eigenvalues.
Authors
* William Aris 2020
* Francois Grondin 2020
"""
import torch
def gevd(a, b=None):
"""This method computes the eigenvectors ... | 11,655 | 26.818616 | 92 | py |
speechbrain | speechbrain-main/speechbrain/processing/__init__.py | """ Package containing various techniques of speech processing
"""
| 67 | 21.666667 | 62 | py |
speechbrain | speechbrain-main/speechbrain/lobes/features.py | """Basic feature pipelines.
Authors
* Mirco Ravanelli 2020
* Peter Plantinga 2020
* Sarthak Yadav 2020
"""
import torch
from speechbrain.processing.features import (
STFT,
spectral_magnitude,
Filterbank,
DCT,
Deltas,
ContextWindow,
)
from speechbrain.nnet.CNN import GaborConv1d
from speechbr... | 14,790 | 32.615909 | 114 | py |
speechbrain | speechbrain-main/speechbrain/lobes/augment.py | """
Combinations of processing algorithms to implement common augmentations.
Examples:
* SpecAugment
* Environmental corruption (noise, reverberation)
Authors
* Peter Plantinga 2020
* Jianyuan Zhong 2020
"""
import os
import torch
import torchaudio
import speechbrain as sb
from speechbrain.utils.data_utils import... | 18,577 | 32.473874 | 102 | py |
speechbrain | speechbrain-main/speechbrain/lobes/downsampling.py | """
Combinations of processing algorithms to implement downsampling methods.
Authors
* Salah Zaiem
"""
import torch
import torchaudio.transforms as T
from speechbrain.nnet.CNN import Conv1d
from speechbrain.nnet.pooling import Pooling1d
class Downsampler(torch.nn.Module):
""" Wrapper for downsampling techniques... | 3,444 | 26.782258 | 80 | py |
speechbrain | speechbrain-main/speechbrain/lobes/__init__.py | """ Package defining common blocks (DNN models, processing ...)
This subpackage gathers higher level blocks, or "lobes".
The classes here may leverage the extended YAML syntax.
"""
from . import models # noqa
| 211 | 29.285714 | 63 | py |
speechbrain | speechbrain-main/speechbrain/lobes/beamform_multimic.py | """Beamformer for multi-mic processing.
Authors
* Nauman Dawalatabad
"""
import torch
from speechbrain.processing.features import (
STFT,
ISTFT,
)
from speechbrain.processing.multi_mic import (
Covariance,
GccPhat,
DelaySum,
)
class DelaySum_Beamformer(torch.nn.Module):
"""Generate beamform... | 1,264 | 22.425926 | 81 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/wav2vec.py | """Components necessary to build a wav2vec 2.0 architecture following the
original paper: https://arxiv.org/abs/2006.11477.
Authors
* Rudolf A Braun 2022
* Guillermo Cambara 2022
* Titouan Parcollet 2022
"""
import logging
import torch
import torch.nn.functional as F
import torch.nn as nn
import random
import numpy a... | 12,989 | 32.916449 | 98 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/conv_tasnet.py | """ Implementation of a popular speech separation model.
"""
import torch
import torch.nn as nn
import speechbrain as sb
import torch.nn.functional as F
from speechbrain.processing.signal_processing import overlap_and_add
EPS = 1e-8
class Encoder(nn.Module):
"""This class learns the adaptive frontend for the Co... | 16,379 | 25.721044 | 88 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/MetricGAN.py | """Generator and discriminator used in MetricGAN
Authors:
* Szu-Wei Fu 2020
"""
import torch
import speechbrain as sb
from torch import nn
from torch.nn.utils import spectral_norm
def xavier_init_layer(
in_size, out_size=None, spec_norm=True, layer_type=nn.Linear, **kwargs
):
"Create a layer with spectral no... | 5,148 | 26.832432 | 81 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/MetricGAN_U.py | """Generator and discriminator used in MetricGAN-U
Authors:
* Szu-Wei Fu 2020
"""
import torch
import speechbrain as sb
from torch import nn
from torch.nn.utils import spectral_norm
def xavier_init_layer(
in_size, out_size=None, spec_norm=True, layer_type=nn.Linear, **kwargs
):
"Create a layer with spectral ... | 5,154 | 25.989529 | 81 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/Tacotron2.py | """
Neural network modules for the Tacotron2 end-to-end neural
Text-to-Speech (TTS) model
Authors
* Georges Abous-Rjeili 2021
* Artem Ploujnikov 2021
"""
# This code uses a significant portion of the NVidia implementation, even though it
# has been modified and enhanced
# https://github.com/NVIDIA/DeepLearningExampl... | 59,832 | 30.441408 | 138 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/segan_model.py | """
This file contains two PyTorch modules which together consist of the SEGAN model architecture
(based on the paper: Pascual et al. https://arxiv.org/pdf/1703.09452.pdf).
Modification of the initialization parameters allows the change of the model described in the class project,
such as turning the generator to a VAE... | 8,123 | 31.496 | 108 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/L2I.py | """This file implements the necessary classes and functions to implement Listen-to-Interpret (L2I) interpretation method from https://arxiv.org/abs/2202.11479v2
Authors
* Cem Subakan 2022
* Francesco Paissan 2022
"""
import torch.nn as nn
import torch.nn.functional as F
import torch
from speechbrain.lobes.models.P... | 11,147 | 29.376022 | 160 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/fairseq_wav2vec.py | """This lobe enables the integration of fairseq pretrained wav2vec models.
Reference: https://arxiv.org/abs/2006.11477
Reference: https://arxiv.org/abs/1904.05862
FairSeq >= 1.0.0 needs to be installed: https://fairseq.readthedocs.io/en/latest/
Authors
* Titouan Parcollet 2021
* Salima Mdhaffar 2021
"""
import tor... | 11,652 | 33.785075 | 105 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/convolution.py | """This is a module to ensemble a convolution (depthwise) encoder with or without residule connection.
Authors
* Jianyuan Zhong 2020
"""
import torch
from speechbrain.nnet.CNN import Conv2d
from speechbrain.nnet.containers import Sequential
from speechbrain.nnet.normalization import LayerNorm
class ConvolutionFront... | 5,520 | 30.369318 | 107 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/ESPnetVGG.py | """This lobes replicate the encoder first introduced in ESPNET v1
source: https://github.com/espnet/espnet/blob/master/espnet/nets/pytorch_backend/rnn/encoders.py
Authors
* Titouan Parcollet 2020
"""
import torch
import speechbrain as sb
class ESPnetVGG(sb.nnet.containers.Sequential):
"""This model is a combin... | 3,675 | 29.131148 | 96 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/EnhanceResnet.py | """Wide ResNet for Speech Enhancement.
Author
* Peter Plantinga 2022
"""
import torch
import speechbrain as sb
from speechbrain.processing.features import STFT, ISTFT, spectral_magnitude
class EnhanceResnet(torch.nn.Module):
"""Model for enhancement based on Wide ResNet.
Full model description at: https://... | 7,571 | 30.160494 | 95 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/ContextNet.py | """The SpeechBrain implementation of ContextNet by
https://arxiv.org/pdf/2005.03191.pdf
Authors
* Jianyuan Zhong 2020
"""
import torch
from torch.nn import Dropout
from speechbrain.nnet.CNN import DepthwiseSeparableConv1d, Conv1d
from speechbrain.nnet.linear import Linear
from speechbrain.nnet.pooling import Adaptive... | 9,388 | 30.612795 | 201 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/Xvector.py | """A popular speaker recognition and diarization model.
Authors
* Nauman Dawalatabad 2020
* Mirco Ravanelli 2020
"""
# import os
import torch # noqa: F401
import torch.nn as nn
import speechbrain as sb
from speechbrain.nnet.pooling import StatisticsPooling
from speechbrain.nnet.CNN import Conv1d
from speechbrain.n... | 6,854 | 28.170213 | 77 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/resepformer.py | """Library for the Reseource-Efficient Sepformer.
Authors
* Cem Subakan 2022
"""
import torch
import torch.nn as nn
from speechbrain.lobes.models.dual_path import select_norm
from speechbrain.lobes.models.transformer.Transformer import (
TransformerEncoder,
PositionalEncoding,
get_lookahead_mask,
)
impor... | 21,609 | 29.013889 | 119 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/huggingface_wav2vec.py | """This lobe enables the integration of huggingface pretrained wav2vec2/hubert/wavlm models.
Reference: https://arxiv.org/abs/2006.11477
Reference: https://arxiv.org/abs/1904.05862
Reference: https://arxiv.org/abs/2110.13900
Transformer from HuggingFace needs to be installed:
https://huggingface.co/transformers/instal... | 18,749 | 36.055336 | 123 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/__init__.py | """ Package defining neural netword models (CRDNN, Xvectors ...)
"""
| 69 | 22.333333 | 64 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/Cnn14.py | """ This file implements the CNN14 model from https://arxiv.org/abs/1912.10211
Authors
* Cem Subakan 2022
* Francesco Paissan 2022
"""
import torch.nn as nn
import torch.nn.functional as F
import torch
def init_layer(layer):
"""Initialize a Linear or Convolutional layer."""
nn.init.xavier_uniform_(layer.... | 7,429 | 30.483051 | 89 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/ECAPA_TDNN.py | """A popular speaker recognition and diarization model.
Authors
* Hwidong Na 2020
"""
# import os
import torch # noqa: F401
import torch.nn as nn
import torch.nn.functional as F
from speechbrain.dataio.dataio import length_to_mask
from speechbrain.nnet.CNN import Conv1d as _Conv1d
from speechbrain.nnet.normalizatio... | 16,703 | 28.050435 | 83 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/VanillaNN.py | """Vanilla Neural Network for simple tests.
Authors
* Elena Rastorgueva 2020
"""
import torch
import speechbrain as sb
class VanillaNN(sb.nnet.containers.Sequential):
"""A simple vanilla Deep Neural Network.
Arguments
---------
activation : torch class
A class used for constructing the activ... | 1,178 | 23.5625 | 60 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/CRDNN.py | """A combination of Convolutional, Recurrent, and Fully-connected networks.
Authors
* Mirco Ravanelli 2020
* Peter Plantinga 2020
* Ju-Chieh Chou 2020
* Titouan Parcollet 2020
* Abdel 2020
"""
import torch
import speechbrain as sb
class CRDNN(sb.nnet.containers.Sequential):
"""This model is a combination of... | 10,521 | 32.724359 | 79 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/HifiGAN.py | """
Neural network modules for the HiFi-GAN: Generative Adversarial Networks for
Efficient and High Fidelity Speech Synthesis
For more details: https://arxiv.org/pdf/2010.05646.pdf
Authors
* Duret Jarod 2021
* Yingzhi WANG 2022
"""
# Adapted from https://github.com/jik876/hifi-gan/ and https://github.com/coqui-ai/... | 37,244 | 28.748403 | 99 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/RNNLM.py | """Implementation of a Recurrent Language Model.
Authors
* Mirco Ravanelli 2020
* Peter Plantinga 2020
* Ju-Chieh Chou 2020
* Titouan Parcollet 2020
* Abdel 2020
"""
import torch
from torch import nn
import speechbrain as sb
class RNNLM(nn.Module):
"""This model is a combination of embedding layer, RNN, DNN... | 3,628 | 28.504065 | 79 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/PIQ.py | """This file implements the necessary classes and functions to implement Posthoc Interpretations via Quantization.
Authors
* Cem Subakan 2023
* Francesco Paissan 2023
"""
import torch
import torch.nn as nn
from torch.autograd import Function
def get_irrelevant_regions(labels, K, num_classes, N_shared=5, stage="TR... | 19,449 | 30.370968 | 273 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/huggingface_whisper.py | """This lobe enables the integration of huggingface pretrained whisper model.
Transformer from HuggingFace needs to be installed:
https://huggingface.co/transformers/installation.html
Authors
* Adel Moumen 2022
* Titouan Parcollet 2022
* Luca Della Libera 2022
"""
import torch
import logging
from torch import nn
... | 12,043 | 35.607903 | 117 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/dual_path.py | """Library to support dual-path speech separation.
Authors
* Cem Subakan 2020
* Mirco Ravanelli 2020
* Samuele Cornell 2020
* Mirko Bronzi 2020
* Jianyuan Zhong 2020
"""
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import copy
from speechbrain.nnet.linear import Linear
from spee... | 42,269 | 28.313454 | 102 | py |
speechbrain | speechbrain-main/speechbrain/lobes/models/g2p/dataio.py | """
Data pipeline elements for the G2P pipeline
Authors
* Loren Lugosch 2020
* Mirco Ravanelli 2020
* Artem Ploujnikov 2021 (minor refactoring only)
"""
from functools import reduce
from speechbrain.wordemb.util import expand_to_chars
import speechbrain as sb
import torch
import re
RE_MULTI_SPACE = re.compile(r"\... | 16,894 | 25.153251 | 84 | py |
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