Masaru Fujieda

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A source signal is estimated using an associative memory model (AMM) and used for separation matrix optimization in linear blind source separation (BSS) to yield high quality and less distorted speech. Linear-filtering-based BSS, such as independent vector analysis (IVA), has been shown to be effective in sound source separation while avoiding non-linear(More)
— This paper presents an improvement method of the multiple pitch estimation algorithm using comb filters. Conventionally the pitch was estimated by using parallel-connected comb filters method (PCF). However, PCF has problems which often fail in the pitch estimation when there is the fundamental frequency of higher tone near harmonics of lower tone.(More)
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