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Portuguese Speech Dataset for recognition task
Dataset comprises 10+ hours of telephone dialogues in Portuguese, collected from 10+ native speakers across various topics and domains. It is 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.
💵 Buy the Dataset: This is a limited preview of the data. To access the full dataset, please contact us at https://unidata.pro to discuss your requirements and pricing options.
- 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
How was Portuguese speech data collected?
The recordings were collected through crowdsourcing platforms, allowing the dataset to include authentic telephone conversations from Portuguese speakers.
What type of conversations are included in this dataset?
The dataset contains real telephone dialogues in Portuguese recorded in conversational scenarios. These natural interactions provide examples of continuous speech and dialogue structure, making the data useful for developing AI systems that need to understand everyday Portuguese communication.
Who can benefit from this Portuguese speech recognition dataset?
The dataset is useful for speech technology companies, AI researchers, universities, conversational AI developers, and organizations creating Portuguese-language voice applications. It can support projects involving automatic speech recognition, transcription, voice assistants, call analysis, and natural language processing."
This dataset is a valuable resource for researchers and developers working on speech recognition, language models, and speech technology.
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