Tamil (India) In-car Speech Dataset

The audio dataset comprises recordings of wake words and commands specific to in-car activities, featuring native Tamil speakers from India. It includes speech data, detailed metadata, and accurate transcriptions.

Category

In-Car Prompt Recordings

Total Volume

5000+ prompts

Last updated

Aug 2024

Number of participants

50+

Tamil In-car speech dataset

About this Off-the-shelf Speech Dataset

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Introduction

Welcome to the Tamil Language In-car Speech Dataset, a comprehensive collection of audio recordings designed to facilitate the development of speech recognition models specifically tailored for in-car environments. This dataset aims to support research and innovation in automotive speech technology, enabling seamless and robust voice interactions within vehicles for drivers and co-passengers.

Speech Data

This dataset comprises over 5,000 high-quality audio recordings collected from various in-car environments. These recordings include scripted wake words and command-type prompts.

  • Participant Diversity:
  • Speakers: 50+ native Tamil speakers from the FutureBeeAI Community.
  • Regions: Ensures a balanced representation of Tamil accents, dialects, and demographics.
  • Participant Profile: Participants range from 18 to 70 years old, representing both males and females in a 60:40 ratio, respectively.
  • Recording Nature: Scripted wake word and command type of audio recordings.
  • Duration: Average duration of 5 to 20 seconds per audio recording.
  • Formats: WAV format with mono channels, a bit depth of 16 bits. The dataset contains different data at 16kHz and 48kHz.
  • Dataset Diversity

    Apart from participant diversity, the dataset is diverse in terms of different wake words, voice commands, and recording environments.

  • Different Automobile Related Wake Words: Hey Mercedes, Hey BMW, Hey Porsche, Hey Volvo, Hey Audi, Hi Genesis, Hey Mini, Hey Toyota, Ok Ford, Hey Hyundai, Ok Honda, Hello Kia, Hey Dodge.
  • Different Cars: Data collection was carried out in different types and models of cars.
  • Different Types of Voice Commands:
  • Navigational Voice Commands
  • Mobile Control Voice Commands
  • Car Control Voice Commands
  • Multimedia & Entertainment Commands
  • General, Question Answer, Search Commands
  • Recording Time: Participants recorded the given prompts at various times to make the dataset more diverse.
  • Morning
  • Afternoon
  • Evening
  • Recording Environment: Various recording environments were captured to acquire more realistic data and to make the dataset inclusive of various types of noises. Some of the environment variables are as follows:
  • Noise Level: Silent, Low Noise, Moderate Noise, High Noise
  • Parking Location: Indoor, Outdoor
  • Car Windows: Open, Closed
  • Car AC: On, Off
  • Car Engine: On, Off
  • Car Movement: Stationary, Moving
  • Metadata

    The dataset provides comprehensive metadata for each audio recording and participant:

  • Participant Metadata: Unique identifier, age, gender, country, state, district, accent, and dialect.
  • Other Metadata: Recording transcript, recording environment, device details, sample rate, bit depth, file format, recording time.
  • This metadata is a powerful tool for understanding and characterizing the data, enabling informed decision-making in the development of Tamil voice assistant speech recognition models.

    Usage and Applications

    This In-car Speech Dataset is a valuable resource for various applications in the field of in-car voice recognition and AI-driven voice technology. This dataset can be leveraged to enhance the performance and functionality of voice-activated systems across different domains.

  • Speech Recognition Model Training: Provides high-quality audio data for training models to accurately recognize and respond to in-car voice commands.
  • Safety and Emergency Response: Supports the development of systems that recognize and respond to emergency commands and safety alerts.
  • Driver Assistance: Facilitates the creation of advanced driver-assistance systems (ADAS) that leverage voice commands for hands-free operation.
  • Secure and Ethical Collection

  • Our proprietary data collection platform, “Yugo,” was used throughout the process of this dataset creation.
  • Throughout the data collection process, the data remained within our secure platform and did not leave our environment, ensuring data security and confidentiality.
  • The data collection process adhered to strict ethical guidelines, ensuring the privacy and consent of all participants.
  • It does not include any personally identifiable information about any participant, which makes the dataset safe to use.
  • Updates and Customization

    Understanding the importance of diverse environments for robust voice assistant models, our in-car voice dataset is regularly updated with new audio data captured in various real-world conditions.

  • Customization & Custom Collection Options:
  • Environmental Conditions: Custom collection in specific environmental conditions upon request.
  • Sample Rates: Customizable from 8kHz to 48kHz.
  • Diverse Pace: Custom collection can be done at a diverse pace upon request.
  • Device Specific: Recording can be done with the specific mobile brand or operating system.
  • License

    This TamilIn-car audio dataset is created by FutureBeeAI and is available for commercial use.

    Use Cases

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    In-car ASR

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    Driver Assistance

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    Conversational AI

    Dataset Sample(s)

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    Dataset Details

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    Language

    Tamil

    Language code

    ta-in

    Country

    India

    Accents

    Kongu Tamil, Madras Bashai ...more

    Gender Distribution

    M:60, F:40

    Age Group

    18-70

    File Details

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    Environment

    Silent & Noisy

    Bit Depth

    16 bit

    Sample rate

    16KHz & 48 KHz

    Channel

    Mono

    Audio file duration

    5 to 20 seconds

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    Prompt 2 Bg
    In-Car Speech Dataset: Tamil (India)