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Yoichi Yamashita

5 accepted papers

2024

Environmental Sound Synthesis from Vocal Imitations and Sound Event Labels

Yuki Okamoto, Keisuke Imoto, Shinnosuke Takamichi, Ryotaro Nagase, Takahiro Fukumori, Yoichi Yamashita
ICASSP 2024accepted

One way of expressing an environmental sound is using vocal imitations, which involve the process of replicating or mimicking the rhythm and pitch of sounds by voice. We can effectively express the features of environmental sounds, such as rhythm and pitch, using vocal imitations, which cannot be ex…

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2022

Sound Event Detection Guided by Semantic Contexts of Scenes

Noriyuki Tonami, Keisuke Imoto, Ryotaro Nagase, Yuki Okamoto, Takahiro Fukumori, Yoichi Yamashita
ICASSP 2022accepted

Some studies have revealed that contexts of scenes (e.g., "home," "office," and "cooking") are advantageous for sound event detection (SED). Mobile devices and sensing technologies give useful information on scenes for SED without the use of acoustic signals. However, conventional methods can employ…

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2021

Sound Event Detection Based on Curriculum Learning Considering Learning Difficulty of Events

Noriyuki Tonami, Keisuke Imoto, Yuki Okamoto, Takahiro Fukumori, Yoichi Yamashita
ICASSP 2021accepted

In conventional sound event detection (SED) models, two types of events, namely, those that are present and those that do not occur in an acoustic scene, are regarded as the same type of the events. The conventional SED methods cannot effectively exploit the difference between the two types of event…

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2020

Sound Event Detection by Multitask Learning of Sound Events and Scenes with Soft Scene Labels

Keisuke Imoto, Noriyuki Tonami, Yuma Koizumi, Masahiro Yasuda, Ryosuke Yamanishi, Yoichi Yamashita
ICASSP 2020accepted

Sound event detection (SED) and acoustic scene classification (ASC) are major tasks in environmental sound analysis. Considering that sound events and scenes are closely related to each other, some works have addressed joint analyses of sound events and acoustic scenes based on multitask learning (M…

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2017

Phase reconstruction method based on time-frequency domain harmonic structure for speech enhancement

Yukoh Wakabayashi, Takahiro Fukumori, Masato Nakayama, Takanobu Nishiura, Yoichi Yamashita
ICASSP 2017accepted

Speech enhancement in noisy environments has been widely investigated by modifying only the amplitude spectrum of the speech signal, while the phase spectrum, which is regarded as an unimportant feature, is ignored. However, it has recently been reported that the phase spectrum plays an important ro…

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