This CSTR VCTK Corpus includes speech data uttered by 110 English speakers with various accents. Each speaker reads out about 400 sentences, which were selected from a newspaper, the rainbow passage and an elicitation paragraph used for the speech accent archive. The newspaper texts were taken from Herald Glasgow, with permission from Herald & Times Group. Each speaker has a different set of the newspaper texts selected based a greedy algorithm that increases the contextual and phonetic coverage. The details of the text selection algorithms are described in the following paper: C. Veaux, J. Yamagishi and S. King, "The voice bank corpus: Design, collection and data analysis of a large regional accent speech database," https://doi.org/10.1109/ICSDA.2013.6709856. The rainbow passage and elicitation paragraph are the same for all speakers. The rainbow passage can be found at International Dialects of English Archive: (http://web.ku.edu/~idea/readings/rainbow.htm). The elicitation paragraph is identical to the one used for the speech accent archive (http://accent.gmu.edu). The details of the the speech accent archive can be found at http://www.ualberta.ca/~aacl2009/PDFs/WeinbergerKunath2009AACL.pdf. All speech data was recorded using an identical recording setup: an omni-directional microphone (DPA 4035) and a small diaphragm condenser microphone with very wide bandwidth (Sennheiser MKH 800), 96kHz sampling frequency at 24 bits and in a hemi-anechoic chamber of the University of Edinburgh. (However, two speakers, p280 and p315 had technical issues of the audio recordings using MKH 800). All recordings were converted into 16 bits, were downsampled to 48 kHz, and were manually end-pointed. Source: CSTR VCTK Corpus: English Multi-speaker Corpus for CSTR Voice Cloning Toolkit (version 0.92)
This is the forehead accelerometer variant of the VibraVox dataset. VibraVox aims at serving as a valuable resource for advancing the field of body-conducted speech analysis and facilitating the development of robust communication systems for real-world applications. This dataset, available on HuggingFace can be used for various audio machine learning tasks : - Automatic Speech Recognition (ASR) (Speech-to-Text , Speech-to-Phoneme) - Audio Bandwidth Extension (BWE) - Speaker Verification (SPKV) / identification - Voice cloning - etc ... The VibraVox dataset speech corpus has been released in July 2024. It includes french speech recorded simultaneously using multiple audio and vibration sensors : a forehead miniature vibration sensor, an in-ear comply foam-embedded microphone, an in-ear rigid earpiece-embedded microphone, a temple vibration pickup, a headset microphone located near the mouth, and a laryngophone. VibraVox has been recorded with 200 participants under various acoustic conditions imposed by a 5th order ambisonics spatialization sphere.
This is the in-ear rigid earpiece-embedded microphone variant of the VibraVox dataset. VibraVox aims at serving as a valuable resource for advancing the field of body-conducted speech analysis and facilitating the development of robust communication systems for real-world applications. This dataset, available on HuggingFace can be used for various audio machine learning tasks : - Automatic Speech Recognition (ASR) (Speech-to-Text , Speech-to-Phoneme) - Audio Bandwidth Extension (BWE) - Speaker Verification (SPKV) / identification - Voice cloning - etc ... The VibraVox dataset speech corpus has been released in July 2024. It includes french speech recorded simultaneously using multiple audio and vibration sensors : a forehead miniature vibration sensor, an in-ear comply foam-embedded microphone, an in-ear rigid earpiece-embedded microphone, a temple vibration pickup, a headset microphone located near the mouth, and a laryngophone. VibraVox has been recorded with 200 participants under various acoustic conditions imposed by a 5th order ambisonics spatialization sphere.
This is the in-ear comply foam-embedded microphone variant of the VibraVox dataset. VibraVox aims at serving as a valuable resource for advancing the field of body-conducted speech analysis and facilitating the development of robust communication systems for real-world applications. This dataset, available on HuggingFace can be used for various audio machine learning tasks : - Automatic Speech Recognition (ASR) (Speech-to-Text , Speech-to-Phoneme) - Audio Bandwidth Extension (BWE) - Speaker Verification (SPKV) / identification - Voice cloning - etc ... The VibraVox dataset speech corpus has been released in July 2024. It includes french speech recorded simultaneously using multiple audio and vibration sensors : a forehead miniature vibration sensor, an in-ear comply foam-embedded microphone, an in-ear rigid earpiece-embedded microphone, a temple vibration pickup, a headset microphone located near the mouth, and a laryngophone. VibraVox has been recorded with 200 participants under various acoustic conditions imposed by a 5th order ambisonics spatialization sphere.
This is the temple vibration pickup variant of the VibraVox dataset. VibraVox aims at serving as a valuable resource for advancing the field of body-conducted speech analysis and facilitating the development of robust communication systems for real-world applications. This dataset, available on HuggingFace can be used for various audio machine learning tasks : - Automatic Speech Recognition (ASR) (Speech-to-Text , Speech-to-Phoneme) - Audio Bandwidth Extension (BWE) - Speaker Verification (SPKV) / identification - Voice cloning - etc ... The VibraVox dataset speech corpus has been released in July 2024. It includes french speech recorded simultaneously using multiple audio and vibration sensors : a forehead miniature vibration sensor, an in-ear comply foam-embedded microphone, an in-ear rigid earpiece-embedded microphone, a temple vibration pickup, a headset microphone located near the mouth, and a laryngophone. VibraVox has been recorded with 200 participants under various acoustic conditions imposed by a 5th order ambisonics spatialization sphere.
This is the throat microphone (laryngophone) variant of the VibraVox dataset. VibraVox aims at serving as a valuable resource for advancing the field of body-conducted speech analysis and facilitating the development of robust communication systems for real-world applications. This dataset, available on HuggingFace can be used for various audio machine learning tasks : - Automatic Speech Recognition (ASR) (Speech-to-Text , Speech-to-Phoneme) - Audio Bandwidth Extension (BWE) - Speaker Verification (SPKV) / identification - Voice cloning - etc ... The VibraVox dataset speech corpus has been released in July 2024. It includes french speech recorded simultaneously using multiple audio and vibration sensors : a forehead miniature vibration sensor, an in-ear comply foam-embedded microphone, an in-ear rigid earpiece-embedded microphone, a temple vibration pickup, a headset microphone located near the mouth, and a laryngophone. VibraVox has been recorded with 200 participants under various acoustic conditions imposed by a 5th order ambisonics spatialization sphere.