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Russian Speech Recognition Dataset

The dataset includes 338 hours of telephone dialogues in Russian from 460 native speakers, offering high-quality audio recordings with detailed annotations (text, speaker ID, gender, age) to support speech recognition systems, natural language processing, and deep learning models for building accurate Russian dialogue and audio datasets

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  • Hours
    338
  • Speakers
    460
  • Word Accuracy Rate
    98%
  • NLP
  • LLM
  • Machine Learning
  • Audio Processing
  • ASR
  • Voice Recognition
  • Hours
    338
  • Speakers
    460
  • Word Accuracy Rate
    98%

Dataset Info

Characteristic Data
Description Audio of telephone dialogues in Russian for training NLP models in real-world conversational scenarios.
Data types Audio
Tasks Speech recognition, NLP
Country Russia(RUS)
Hours of telephone dialogue 338
Number of speakers 460
Labeling Annotation (text content, speaker's ID, gender, age and other attributes)
Gender Male (46%), Female (54%)
Recording device Android smartphone, iPhone
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Statistics

Distribution by gender

Technical
Characteristics

Characteristic Data
Audio Format Wav
Sampling Rate 16kHz
Number of Channels Mono
Bit Depth 16 bit
Recording condition Low background noise (indoor)
Source and collection methodology: Data was collected by a partner of Unidata.

Dataset Use Cases

  • Call Centers & Customer Service

    Improving Russian Telephone Dialogue Recognition

    Russian Speech Recognition Dataset includes authentic audio recordings from real conversations. Speech samples covering various accents and natural speaking patterns support recognition systems in call centers. Companies use it to enhance automatic speech recognition, reduce transcription errors, and improve customer interactions in Russian-speaking markets.

  • AI & Machine Learning Research

    Training Models for Russian Speech Processing

    This speech recognition dataset provides training data for machine learning and deep learning models. The dataset consists of high-quality audio files and accurate transcriptions collected from native speakers. Researchers rely on it to build recognition technology capable of transcribing speech and handling diverse speech signals with high accuracy.

  • Multilingual Applications

    Supporting Speech Translation and Cross-Language Models

    These datasets are widely used in multilingual speech projects. By combining speech samples from Russian with other languages, developers can create natural language translation tools and language processing systems. Its diverse dataset ensures adaptability for speech technology in cross-lingual communication and global recognition systems.

  • Commercial & Industrial Use

    Deploying Russian Dialogue Recognition in Real Scenarios

    Businesses apply the Russian dialogue dataset in commercial use cases such as transcription platforms, smart assistants, and telephone speech services. Since the database contains a diverse range of speakers, accents, and conditions, it enables recognition technology with improved audio quality, delivering reliable results in speech processing across industries.

How diverse is Russian Speech Recognition Dataset?
The dataset includes 460 speakers, with 46% male and 54% female, covering a diverse range of ages and various accents. This diversity ensures higher accuracy when training recognition models for real-world Russian speech scenarios.
What should I consider before buying this dataset?
When purchasing it, consider the audio format, sampling rate, and the diversity of native Russian speakers included. Ensure the annotations and speech samples match your project’s needs in speech recognition, NLP, or deep learning models.
Can I request a sample of Russian Speech Recognition Dataset before purchasing or downloading it?
Yes, a sample of the dataset can be provided. This allows you to evaluate audio quality, transcriptions, and speaker metadata before committing to a full purchase.
What are the sources of data for Unidata datasets?
Unidata datasets are created through structured data collection with trusted partners. This dataset was recorded by native speakers in indoor environments with low background noise, ensuring high-quality audio recordings.
Still have questions about using Unidata datasets? Read our user-guides

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