activity
20182023
most citedUnsupervised Detection of Anomalous Sound based on Deep Learning and the Neyman-Pearson Lemma

143 citations · 511 across the 26 of their papers we have counts for

collaborators
Showing 2020Show all

5 papers · 1 filter

eess.AS2020★ 11 cited

Effects of Word-frequency based Pre- and Post- Processings for Audio Captioning

Daiki Takeuchi, Yuma Koizumi, Yasunori Ohishi +2

The system we used for Task 6 (Automated Audio Captioning)of the Detection and Classification of Acoustic Scenes and Events(DCASE) 2020 Challenge combines three elements, namely, d…

eess.AS2020★ 21 cited

The NTT DCASE2020 Challenge Task 6 system: Automated Audio Captioning with Keywords and Sentence Length Estimation

Yuma Koizumi, Daiki Takeuchi, Yasunori Ohishi +2

This technical report describes the system participating to the Detection and Classification of Acoustic Scenes and Events (DCASE) 2020 Challenge, Task 6: automated audio captionin…

eess.AS2020★ 105 cited

Description and Discussion on DCASE2020 Challenge Task2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring

Yuma Koizumi, Yohei Kawaguchi, Keisuke Imoto +8

In this paper, we present the task description and discuss the results of the DCASE 2020 Challenge Task 2: Unsupervised Detection of Anomalous Sounds for Machine Condition Monitori…

eess.AS2020★ 5 cited

Real-time speech enhancement using equilibriated RNN

Daiki Takeuchi, Kohei Yatabe, Yuma Koizumi +2

We propose a speech enhancement method using a causal deep neural network~(DNN) for real-time applications. DNN has been widely used for estimating a time-frequency~(T-F) mask whic…

eess.AS2020★ 5 cited

Phase reconstruction based on recurrent phase unwrapping with deep neural networks

Yoshiki Masuyama, Kohei Yatabe, Yuma Koizumi +2

Phase reconstruction, which estimates phase from a given amplitude spectrogram, is an active research field in acoustical signal processing with many applications including audio s…