Speaker-Independent Spectral Enhancement for Bone-Conducted Speech

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words

Model-based speech enhancement using a bone-conducted signal.

Codebook-based single-microphone noise suppressors, which exploit prior knowledge about speech and noise statistics, provide better performance in nonstationary noise. However, as the enhancement involves a joint optimization over speech and noise codebooks, this results in high computational complexity. A codebook-based method is proposed that uses a reference signal observed by a bone-conduct...

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words

Reconstruction filter design for bone-conducted speech

Bone-conducted speech is of low intelligibility, but its quality is not affected by noise. In this paper, we take into account such propertes of bone-conducted speech, and address a digital filter to reconstruct the quality of the bone-conducted speech signal obtained from a speaker. The reconstruction filter design method is derived based on a model assumption of pronunciation. Experimental re...

Combining missing-feature theory, speech enhancement and speaker-dependent/-independent modeling for speech separation

This paper considers the recognition of speech given in the form of two mixed sentences, spoken by the same talker or by two different talkers. The database published on the ICSLP’2006 website for Two-Talker Speech Separation Challenge is used in the study. A system that recognizes and reconstructs both sentences from the given mixture is described. The system involves a combination of several ...