Abstract : We present an example of an anthropomorphic approach, in which auditory-based cues are combined with temporal correlation to implement a source separation system. The auditory features are based on spectral amplitudemodulation and energy information obtained through 256 cochlear filters. Segmentation and binding of auditory objects are performed with a two-layered spiking neural network. The first layer performs the segmentation of the auditory images into objects, while the second layer binds the auditory objects belonging to the same source. The binding is further used to generate a mask (binary gain) to suppress the undesired sources fromthe original signal. Results are presented for a double-voiced (2 speakers) speech segment...
A person with normal hearing has the ability to follow a particular conversation of interest in a no...
Enhancing quality of speech in noisy environments has been an active area of research due to the abu...
While humans can easily segregate and track a speaker's voice in a loud noisy environment, most mode...
Wepresent an example of an anthropomorphic approach, in which auditory-based cues are combined with ...
Abstract. A sound source separation technique based on a bio-inspired neural network, capable of fun...
Multiple sound sources often contain harmonics that overlap and may be degraded by environmental noi...
The high levels goals of this thesis are to: understand the neural representation of sound, produce ...
A two-layer spiking neural network is used to segregate double vowels. The first layer is a partiall...
In environments with multiple sound sources, the auditory system is capable of teasing apart the imp...
The objective of this paper is to recover the original component signals from a mixture audio with t...
International audienceIn this work we present a method to perform a complete audiovisual source sepa...
International audienceLooking at the speaker's face is useful to hear better a speech signal and ext...
The human auditory system has the ability to segregate complex auditory scenes into a foreground com...
Tutorial on auditory scene analysis and source separation in humans and machines
The human auditory system performs many remarkable feats; we only fully appreciate how sophisticated...
A person with normal hearing has the ability to follow a particular conversation of interest in a no...
Enhancing quality of speech in noisy environments has been an active area of research due to the abu...
While humans can easily segregate and track a speaker's voice in a loud noisy environment, most mode...
Wepresent an example of an anthropomorphic approach, in which auditory-based cues are combined with ...
Abstract. A sound source separation technique based on a bio-inspired neural network, capable of fun...
Multiple sound sources often contain harmonics that overlap and may be degraded by environmental noi...
The high levels goals of this thesis are to: understand the neural representation of sound, produce ...
A two-layer spiking neural network is used to segregate double vowels. The first layer is a partiall...
In environments with multiple sound sources, the auditory system is capable of teasing apart the imp...
The objective of this paper is to recover the original component signals from a mixture audio with t...
International audienceIn this work we present a method to perform a complete audiovisual source sepa...
International audienceLooking at the speaker's face is useful to hear better a speech signal and ext...
The human auditory system has the ability to segregate complex auditory scenes into a foreground com...
Tutorial on auditory scene analysis and source separation in humans and machines
The human auditory system performs many remarkable feats; we only fully appreciate how sophisticated...
A person with normal hearing has the ability to follow a particular conversation of interest in a no...
Enhancing quality of speech in noisy environments has been an active area of research due to the abu...
While humans can easily segregate and track a speaker's voice in a loud noisy environment, most mode...