ID int64 1 5 | Audio stringclasses 5
values | Text stringclasses 5
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 |
German Speech Dataset for recognition task
Dataset comprises 431 hours of telephone dialogues in German, collected from 590+ native speakers across various topics and domains, achieving an impressive 95% sentence accuracy rate. It is designed for research in automatic speech recognition (ASR) systems.
By utilizing this dataset, researchers and developers can advance their understanding and capabilities in transcribing audio, and natural language processing (NLP). - Get the data
The dataset contains diverse audio files that represent different accents and dialects, making it a comprehensive resource for training and evaluating recognition models.
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Metadata for the dataset
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- 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 types of recordings are included in this German speech recognition dataset?
This German speech recognition dataset contains real-world telephone dialogues between native German speakers. The recordings capture natural conversational speech, making the dataset suitable for automatic speech recognition (ASR), natural language processing (NLP), and conversational AI applications.
What recording devices were used?
The recordings were captured using Android smartphones and iPhones, reflecting real-world telephone communication. Recording speech from multiple device types helps improve the robustness of speech recognition models across different audio sources.
What recording conditions were used?
The recordings were collected indoors under low-background-noise conditions. These controlled recording conditions provide high-quality conversational speech while preserving the characteristics of real telephone communication.
This dataset is essential for anyone looking to improve speech recognition technology and develop more effective automatic speech systems.
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