Speaker Separation
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Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation
The majority of the previous methods have formulated the separation problem through the time-frequency representation of the mixed signal, which has several drawbacks, including the decoupling of the phase and magnitude of the signal, the suboptimality of time-frequency representation for speech separation, and the long latency in calculating the spectrograms.
VoiceFilter: Targeted Voice Separation by Speaker-Conditioned Spectrogram Masking
In this paper, we present a novel system that separates the voice of a target speaker from multi-speaker signals, by making use of a reference signal from the target speaker.
SPEAKER RECOGNITION SPEAKER SEPARATION SPEECH ENHANCEMENT SPEECH RECOGNITION
Monaural Audio Speaker Separation with Source Contrastive Estimation
Although the matrix determined by the output weights is dependent on a set of known speakers, we only use the input vectors during inference.
Single-Channel Multi-Speaker Separation using Deep Clustering
In this paper we extend the baseline system with an end-to-end signal approximation objective that greatly improves performance on a challenging speech separation.