Abstract
The human auditory system has the ability to segregate complex auditory scenes into a foreground component and a background, allowing us to listen to specific speech sounds from a mixture of sounds. Selective attention plays a crucial role in this process, colloquially known as the “cocktail party effect.” It has not been possible to build a machine that can emulate this human ability in real-time. Here, we have developed a framework for the implementation of a neuromorphic sound segregation algorithm in a Field Programmable Gate Array (FPGA). This algorithm is based on the principles of temporal coherence and uses an attention signal to separate a target sound stream from background noise. Temporal coherence implies that auditory features belonging to the same sound source are coherently modulated and evoke highly correlated neural response patterns. The basis for this form of sound segregation is that responses from pairs of channels that are strongly positively correlated belong to the same stream, while channels that are uncorrelated or anti-correlated belong to different streams. In our framework, we have used a neuromorphic cochlea as a frontend sound analyser to extract spatial information of the sound input, which then passes through band pass filters that extract the sound envelope at various modulation rates. Further stages include feature extraction and mask generation, which is finally used to reconstruct the targeted sound. Using sample tonal and speech mixtures, we show that our FPGA architecture is able to segregate sound sources in real-time. The accuracy of segregation is indicated by the high signal-to-noise ratio (SNR) of the segregated stream (90, 77, and 55 dB for simple tone, complex tone, and speech, respectively) as compared to the SNR of the mixture waveform (0 dB). This system may be easily extended for the segregation of complex speech signals, and may thus find various applications in electronic devices such as for sound segregation and speech recognition.
Highlights
Humans can segregate sound sources and focus their attention on specific sounds, while filtering out a range of other background sounds with ease (Bregman, 1990)
This attentional ability is known as the “cocktail party effect” (Cherry, 1953), for it enables one to focus on a single conversation in a noisy room
Different locations on the basilar membrane (BM) of the cochlea vibrate in response to specific sound frequencies, enabling the cochlea to function as a frequency spectrum analyser (Gold and Pumphrey, 1948; Plomp, 1964)
Summary
Humans can segregate sound sources and focus their attention on specific sounds, while filtering out a range of other background sounds with ease (Bregman, 1990). This attentional ability is known as the “cocktail party effect” (Cherry, 1953), for it enables one to focus on a single conversation in a noisy room. Different locations on the basilar membrane (BM) of the cochlea vibrate in response to specific sound frequencies, enabling the cochlea to function as a frequency spectrum analyser (Gold and Pumphrey, 1948; Plomp, 1964). Subsequent processing in the brain includes pitch perception for complex tones (Hall and Plack, 2009), sound localisation (Grothe et al, 2010), sound segregation (Carlyon, 2004) and identification (Alain et al, 2001)
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