Commercial

Hindi Speech Recognition Dataset

The dataset comprises 760 hours of telephone dialogues in Hindi, collected from 1,000+ native speakers across various topics and domains

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  • Hours
    760
  • Speakers
    1,000+
  • Sentence Accuracy Rate
    95%
  • NLP
  • LLM
  • Machine Learning
  • Audio Processing
  • ASR
  • Voice Recognition
  • Hours
    760
  • Speakers
    1,000+
  • Sentence Accuracy Rate
    95%

Dataset Info

Characteristic Data
Description Audio of telephone dialogues in Hindi for training NLP models in real-world conversational scenarios.
Data types Audio
Tasks Speech recognition, NLP
Country India(IND)
Hours of telephone dialogue 760
Number of speakers 1,004
Labeling Annotation (text content, speaker's ID, gender, age and other attributes)
Gender Male (48%), Female (52%)
Recording device Telephone
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Statistics

Distribution by gender
Distribution by gender

Technical
Characteristics

Characteristic Data
Audio Format PCM, a-law/u-law
Sampling Rate 8kHz
Number of Channels Mono
Bit Depth 8 bit
Recording condition Low background noise (indoor)
Source and collection methodolog: Data was collected by a partner of Unidata.

Industries

Entertainment Industry

  • Natural Language Processing:

    Developing and refining NLP models for applications in chatbots, virtual assistants, and conversational agents.

  • Voice Recognition Systems:

    Enhancing customer service automation and improving user experience through accurate speech recognition in telephone dialogues.

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Education

  • Language Learning Tools:

    Providing authentic conversational data to support language acquisition and improve teaching methodologies.

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Dataset Use Cases

  • Call Centers & Customer Service

    Improving Hindi Telephone Dialogue Recognition

    Hindi Speech Recognition Dataset offers real audio recordings from everyday conversations. Since the dataset consists of Hindi speakers with varied accents, it helps call centers train recognition systems to handle diverse voices. This supports more accurate transcription, quicker responses, and better customer service across industries using speech recognition.

  • AI & Machine Learning Research

    Building Models for Hindi Speech Processing

    This Hindi language dataset provides training data for machine learning and deep learning projects. The speech corpus includes high-quality audio files with accurate transcriptions collected from native speakers. Researchers use it to train recognition systems that can process Indian languages with the highest accuracy in transcription and classification tasks.

  • Multilingual Applications

    Supporting Cross-Language NLP and Translation

    The Hindi audio dataset plays a key role in multilingual speech applications. When combined with spoken English and other Indian languages, it enables better language processing, speech translation, and recognition technology. Its large collection of audio samples ensures adaptability for global NLP tasks and multilingual communication systems.

  • Commercial & Industrial Use

    Deploying Hindi Dialogue Recognition at Scale

    Businesses rely on the Hindi dialogue dataset for commercial use in transcription services, smart assistants, and mobile applications. Since the database contains audio samples across varied conditions, it improves recognition systems’ performance, ensuring reliable speech recognition technology for everyday business operations and customer-facing products.

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