Automatic Phoneme Recognition (APR) involves converting spoken language into a sequence of phonemes, which are the distinct units of sound that distinguish one word from another in a given language. It is designed to transcribe spoken words into their textual phonetic representations in real-time, enabling detailed analysis of speech patterns, pronunciation, and linguistic nuances. The goal of Automatic Phoneme Recognition is to accurately identify and transcribe phonemes, considering variations in accent, pronunciation, and speaking style, as well as background noise and other factors that can affect speech quality. This technology is crucial for linguistic research, speech therapy, language learning applications, and enhancing the performance of speech recognition systems.
데이터셋
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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 reference headset 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 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.