Naslov
Cochlea-inspired speech recognition interface

Autori
Russo, Mladen ; Stella, Maja ; Sikora, Marjan ; Šarić, Matko

Izvornik
Medical & biological engineering & computing (0140-0118) 57 (2019), 6; 1393-1403

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
speech recognition interface ; biophysical cochlear model ; noise robustness

Sažetak
Automatic speech recognition (ASR) technology provides a natural interface for human-machine interaction. Typical ASR systems can achieve high performance in quiet environments but, unlike humans, perform poorly in real- world situations. To better simulate the human auditory periphery and improve the performance in realistic noisy scenarios, we propose two models of speech recognition front-ends based on a biophysical cochlear model. The first front-end is based on the method of signal reconstruction from a basilar membrane response. When applied to noisy speech, this method results in improved signal quality. This method can be used as a preprocessing step in a standard ASR system and can also be used as a noise reduction technique for other applications. The second front-end we propose is based on the construction of speech recognition coefficients directly from a basilar membrane response. Experimental results using a continuous-density hidden Markov model (HMM) recognizer demonstrate significant improvement in performance compared to standard Mel- frequency cepstral coefficients (MFCC) in various types of noisy conditions.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti

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