Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
This paper proposes a joint verification-localization structure based on split-band analysis of speech signal and the mixed voicing level. To address the problems in reverberant acoustic environments, a new fundamental frequency estimation algorithm is proposed based on high resolution spectral estimation. In the reconstruction of the distorted speech this information is utilized to reduce the side effect of acoustic noise on the voicing parts. A speaker verification system examines the features of the reconstructed speech in order to authorize the speaker before localization. This procedure prevents localization and beamforming for non-speech and specially the unwanted speakers in multi-speaker scenarios. The verification is implemented with the Gaussian Mixture Model and a new filtering scheme is proposed based on the voicing likelihood of each frequency band measured in the previous steps for efficient localization of the authorized speaker. The performance of the proposed VSL (verified speaker localization) front-end is evaluated in various reverberant and noisy environments. The VSL is utilized in the development of distant-talking automatic speech recognition by microphone array where the system can lock on a specific source and hence the recognition quality improves noticeably.
Mathew Magimai Doss, Subrahmanya Pavankumar Dubagunta
Petr Motlicek, Hynek Hermansky, Sriram Ganapathy, Amrutha Prasad
Ivo Furno, Alan Howling, Hervé Lissek, Pénélope Leyland, Stanislav Sergeev, Gennady Plyushchev