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Yuya Hosoda

dblp:259/3881 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2023
0000-0003-0687-4326ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Audio and music processing · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Audio and music processing › speech processing
pitch estimation
0.712023
Complex-Domain Pitch Estimation Algorithm for Narrowband Speech Signals · IEEE ACM Trans. Audio Speech Lang. Process. 2023
Audio and music processing
speech processing
0.712023
Complex-Domain Pitch Estimation Algorithm for Narrowband Speech Signals · IEEE ACM Trans. Audio Speech Lang. Process. 2023

Methods — techniques the papers use, named apart from their topics

phase difference analysis · 0.7complex spectrum analysis · 0.7
YearPublicationVenuePosition
2023 Complex-Domain Pitch Estimation Algorithm for Narrowband Speech Signals
abstract
We propose a complex-domain pitch estimation algorithm for narrowband speech signals, which utilizes a complex spectrum containing both amplitude and phase spectrum information. Traditional frequency-domain pitch estimation algorithms assume that a speech signal has a harmonic structure; they estimate a pitch by calculating the distance between the adjacent peaks of the amplitude spectrum corresponding to harmonics. However, only a few peaks can be detected from narrowband speech signals because of their limited bandwidth, resulting in pitch estimation errors. In this article, phase differences between harmonics are utilized as an additional cue for pitch estimation. The phase difference between harmonics refers to the two-step phase difference between successive analysis frames and between the lowest-order harmonic and other harmonics, which is theoretically derived using the pitch. When the phase spectrum for the higher-order harmonic is shifted by the theoretical value, it agrees with the phase spectrum for the lowest-order harmonic. Therefore, for each pitch candidate, the proposed method calculates the shifted phase spectra and combines them with the amplitude spectrum to generate complex spectra. When a pitch candidate is correct, the cumulative sum of the complex spectra is added in the same direction, which emphasizes harmonics even for narrowband speech signals. Results of the objective evaluation show that the proposed method accurately estimates the pitch from narrowband speech signals.
Yuya Hosoda, Arata Kawamura, Youji Iiguni
IEEE ACM Trans. Audio Speech Lang. Process.1