ID int64 1 6 | Audio stringclasses 6
values | Text stringclasses 6
values |
|---|---|---|
1 | audio/1.wav | text/1.txt |
2 | audio/2.wav | text/2.txt |
3 | audio/3.wav | text/3.txt |
4 | audio/4.wav | text/4.txt |
5 | audio/5.wav | text/5.txt |
6 | audio/6.wav | text/6.txt |
Hindi Speech Dataset for recognition task
Dataset comprises 760 hours of telephone dialogues in Hindi, collected from 1,000+ native speakers across various topics and domains. This dataset boasts an impressive 95% sentence accuracy rate, making it a valuable resource for advancing speech recognition technology.
By utilizing this dataset, researchers and developers can advance their understanding and capabilities in automatic speech recognition (ASR) systems, transcribing audio, and natural language processing (NLP). - Get the data
The dataset includes high-quality audio recordings with text transcriptions, making it ideal for training and evaluating speech recognition models.
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Metadata for the dataset
- Audio files: High-quality recordings in WAV format
- Text transcriptions: Accurate and detailed transcripts for each audio segment
- Speaker information: Metadata on native speakers, including gender and etc
- Topics: Diverse domains such as general conversations, business and etc
Frequently Asked Questions
What is this Hindi speech dataset used for?
This dataset is designed for training and evaluating automatic speech recognition (ASR), speech-to-text, natural language processing (NLP), and conversational AI models. It supports the development of voice assistants, transcription systems, call analytics, and other speech-enabled applications.
Who can benefit from dataset?
It is valuable for AI researchers, speech recognition engineers, NLP developers, telecommunications companies, contact center solution providers, voice assistant developers, language technology companies, and academic institutions working on Hindi speech technologies.
How was the Hindi speech data collected?
The dataset was collected through crowdsourcing platforms, where native Hindi speakers participated in real-world telephone conversations. This collection methodology captures natural dialogue patterns that are valuable for training speech recognition and NLP models."
This dataset is essential for anyone looking to improve speech recognition technology and develop more effective automatic speech systems.
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