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Speech recognition, text-to-speech, speaker identification, music classification, audio event detection
2,587 datasets
Yoruba BibleTTS Aligned is a dataset for text-to-speech research, likely containing aligned audio recordings and corresponding text from the Bible in the Yoruba language. It was published on Kaggle, but specific details about its size, creation date, and author are unknown. The dataset's primary purpose appears to be training and evaluating speech synthesis models for Yoruba.
Yoruba BibleTTS Aligned is a dataset for text-to-speech research, likely containing aligned audio recordings and corresponding text passages. It is published on Kaggle, but the specific author, size, and creation details are not provided in the metadata. The title suggests the content is based on biblical text in the Yoruba language, a major language of Nigeria.
Yoruba BibleTTS Aligned - LUK is a dataset published on Kaggle. The title suggests it contains audio recordings and corresponding text for the Gospel of Luke in the Yoruba language, likely aligned for text-to-speech applications. Metadata is minimal; actual content requires verification after download.
Yoruba BibleTTS Aligned - HAG is a dataset published on Kaggle. The title suggests it contains Yoruba language audio and corresponding text, likely for text-to-speech alignment tasks. The dataset's specific size, author, and update details are unknown.
A dataset likely containing aligned text and audio for Yoruba speech synthesis, sourced from the Bible. It is published on Kaggle, but the author, organization, and creation date are unknown. The specific size, format, and alignment methodology require verification after download.
Yoruba BibleTTS Aligned - ZEC is a dataset hosted on Kaggle. The title suggests it contains text and audio data aligned for text-to-speech tasks, likely derived from the Yoruba translation of the Bible. The dataset's specific contents, such as the number of audio clips or the alignment method, require verification after download.
A speech dataset likely containing aligned audio recordings and text from the Yoruba Bible. The dataset is published on Kaggle, but its specific size, creation details, and update history are not provided in the available metadata. Its title suggests it is intended for text-to-speech (TTS) model training and alignment tasks.
Yoruba-language audio and text data from the Gospel of John, likely aligned for text-to-speech model training. The dataset is hosted on Kaggle, but its size, creator, and specific structure are not detailed. Columns and sample data are unknown, requiring download for verification.
Aligned text and audio data for Yoruba Bible text-to-speech synthesis, published on Kaggle. The dataset likely contains paired text transcripts and corresponding audio recordings. Specifics on the number of samples, data collection method, and contributors are not provided in the metadata.
A Kaggle-hosted dataset titled 'Yoruba BibleTTS Aligned - MAT'. The dataset likely contains audio recordings and corresponding text transcripts aligned for text-to-speech tasks, specifically for the Yoruba language using biblical text. The specific volume, creation date, and author are unknown.
An audio-text dataset for the Yoruba language, likely containing aligned recordings and transcriptions. The dataset is sourced from the Gospel of Mark (MRK) and is hosted on Kaggle. The specific collection method, author, and exact size are not detailed in the available metadata.
Yoruba BibleTTS Aligned is a Kaggle dataset likely containing text and audio data for speech synthesis. The title suggests it includes aligned text and audio recordings, possibly from a Bible text-to-speech project for the Yoruba language. Specific details on size, columns, and creation are unavailable from the provided metadata.
Yoruba language audio and text data for the biblical book of 1 Corinthians, likely aligned for text-to-speech model training. The dataset is published on Kaggle, but its size, creator, and update date are unknown. Columns and sample data are unavailable, limiting immediate assessment.
Yoruba BibleTTS Aligned is a dataset for text-to-speech synthesis, likely containing aligned text and audio segments. The dataset is published on Kaggle, but detailed metadata such as author, size, and creation date are unknown. Its content appears to be derived from biblical text in the Yoruba language.
Yoruba BibleTTS Aligned - EPH is a dataset published on Kaggle. The title suggests it contains aligned audio and text data, likely for training text-to-speech models for the Yoruba language. Metadata is minimal; actual content requires verification after download.
Yoruba BibleTTS Aligned likely contains text and audio data for the Yoruba language. The dataset appears to be aligned for text-to-speech applications, suggesting paired Bible verses and corresponding audio clips. It was published on Kaggle, but details on its size, creation date, and author are unknown.
Yoruba BibleTTS Aligned likely contains audio recordings and corresponding text for speech synthesis research. The dataset is published on Kaggle, but its specific size, creation date, and author are unknown. Columns suggest it includes aligned text and audio segments, potentially for training text-to-speech models.
Yoruba BibleTTS Aligned is a dataset for text-to-speech research, published on Kaggle. The title suggests it contains aligned text and audio data, likely derived from biblical text in the Yoruba language. Metadata is minimal; the exact number of samples, audio characteristics, and alignment methodology require verification after download.
A Kaggle dataset titled 'Yoruba BibleTTS Aligned - 1TH'. The title suggests it contains Yoruba language text and corresponding audio, likely aligned for text-to-speech model training. The dataset's author, size, and specific contents are unknown from the provided metadata.
Yoruba BibleTTS Aligned - 2PE is a dataset hosted on Kaggle. The title suggests it contains audio recordings and corresponding text from the Yoruba Bible, likely aligned for text-to-speech model training. The dataset's author, organization, size, and other metadata are unknown.