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EURASIP Journal on Audio, Speech, and Music Processing
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  1. One of the greatest challenges in the development of binaural machine audition systems is the disambiguation between front and back audio sources, particularly in complex spatial audio scenes. The goal of this...

    Authors: Sławomir K. Zieliński, Paweł Antoniuk, Hyunkook Lee and Dale Johnson

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2022 2022:3

    Content type: Empirical Research

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  2. Conventional automatic speech recognition (ASR) and emerging end-to-end (E2E) speech recognition have achieved promising results after being provided with sufficient resources. However, for low-resource langua...

    Authors: Siqing Qin, Longbiao Wang, Sheng Li, Jianwu Dang and Lixin Pan

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2022 2022:2

    Content type: Research

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  3. In this paper, we propose a novel algorithm for blind source extraction (BSE) of a moving acoustic source recorded by multiple microphones. The algorithm is based on independent vector extraction (IVE) where t...

    Authors: Jakub Janský, Zbyněk Koldovský, Jiří Málek, Tomáš Kounovský and Jaroslav Čmejla

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2022 2022:1

    Content type: Research

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  4. With the sharp booming of online live streaming platforms, some anchors seek profits and accumulate popularity by mixing inappropriate content into live programs. After being blacklisted, these anchors even fo...

    Authors: Jiacheng Yao, Jing Zhang, Jiafeng Li and Li Zhuo

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:45

    Content type: Research

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  5. We present an unsupervised domain adaptation (UDA) method for a lip-reading model that is an image-based speech recognition model. Most of conventional UDA methods cannot be applied when the adaptation data co...

    Authors: Yuki Takashima, Ryoichi Takashima, Ryota Tsunoda, Ryo Aihara, Tetsuya Takiguchi, Yasuo Ariki and Nobuaki Motoyama

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:44

    Content type: Research

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  7. Deep learning techniques are currently being applied in automated text-to-speech (TTS) systems, resulting in significant improvements in performance. However, these methods require large amounts of text-speech...

    Authors: Zolzaya Byambadorj, Ryota Nishimura, Altangerel Ayush, Kengo Ohta and Norihide Kitaoka

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:42

    Content type: Research

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  9. Voice conversion is to transform a source speaker to the target one, while keeping the linguistic content unchanged. Recently, one-shot voice conversion gradually becomes a hot topic for its potentially wide r...

    Authors: Fangkun Liu, Hui Wang, Renhua Peng, Chengshi Zheng and Xiaodong Li

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:40

    Content type: Research

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  10. This paper presents a new dataset of measured multichannel room impulse responses (RIRs) named dEchorate. It includes annotations of early echo timings and 3D positions of microphones, real sources, and image ...

    Authors: Diego Di Carlo, Pinchas Tandeitnik, Cedrić Foy, Nancy Bertin, Antoine Deleforge and Sharon Gannot

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:39

    Content type: Empirical Research

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  11. In this paper, a multichannel learning-based network is proposed for sound source separation in reverberant field. The network can be divided into two parts according to the training strategies. In the first s...

    Authors: You-Siang Chen, Zi-Jie Lin and Mingsian R. Bai

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:38

    Content type: Research

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  12. High-quality rendering of spatial sound fields in real-time is becoming increasingly important with the steadily growing interest in virtual and augmented reality technologies. Typically, a spherical microphon...

    Authors: Johannes M. Arend, Tim Lübeck and Christoph Pörschmann

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:37

    Content type: Research

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  13. Measurements of the directivity of acoustic sound sources must be interpolated in almost all cases, either for spatial upsampling to higher resolution representations of the data, for spatial resampling to ano...

    Authors: David Ackermann, Fabian Brinkmann, Franz Zotter, Malte Kob and Stefan Weinzierl

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:36

    Content type: Research

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  14. The acoustic echo cannot be entirely removed by linear adaptive filters due to the nonlinear relationship between the echo and the far-end signal. Usually, a post-processing module is required to further suppr...

    Authors: Hongsheng Chen, Guoliang Chen, Kai Chen and Jing Lu

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:35

    Content type: Research

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  15. Code-switching (CS) refers to the phenomenon of using more than one language in an utterance, and it presents great challenge to automatic speech recognition (ASR) due to the code-switching property in one utt...

    Authors: Yanhua Long, Shuang Wei, Jie Lian and Yijie Li

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:34

    Content type: Research

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  16. Many modern smart devices are equipped with a microphone array and a loudspeaker (or are able to connect to one). Acoustic echo cancellation algorithms, specifically their multi-microphone variants, are essent...

    Authors: Nili Cohen, Gershon Hazan, Boaz Schwartz and Sharon Gannot

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:33

    Content type: Research

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  17. The minimum mean-square error (MMSE)-based noise PSD estimators have been used widely for speech enhancement. However, the MMSE noise PSD estimators assume that the noise signal changes at a slower rate than t...

    Authors: Sujan Kumar Roy and Kuldip K. Paliwal

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:32

    Content type: Research

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  18. The performance of speech recognition systems trained with neutral utterances degrades significantly when these systems are tested with emotional speech. Since everybody can speak emotionally in the real-world...

    Authors: Masoud Geravanchizadeh, Elnaz Forouhandeh and Meysam Bashirpour

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:31

    Content type: Research

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  19. If music is the language of the universe, musical note onsets may be the syllables for this language. Not only do note onsets define the temporal pattern of a musical piece, but their time-frequency characteri...

    Authors: Mina Mounir, Peter Karsmakers and Toon van Waterschoot

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:30

    Content type: Research

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  20. To improve the performance of speech enhancement in a complex noise environment, a joint constrained dictionary learning method for single-channel speech enhancement is proposed, which solves the “cross projec...

    Authors: Linhui Sun, Yunyi Bu, Pingan Li and Zihao Wu

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:29

    Content type: Research

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  21. The last decade brought significant advances in automatic speech recognition (ASR) thanks to the evolution of deep learning methods. ASR systems evolved from pipeline-based systems, that modeled hand-crafted s...

    Authors: Alexandru-Lucian Georgescu, Alessandro Pappalardo, Horia Cucu and Michaela Blott

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:28

    Content type: Review

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  22. Many end-to-end approaches have been proposed to detect predefined keywords. For scenarios of multi-keywords, there are still two bottlenecks that need to be resolved: (1) the distribution of important data th...

    Authors: Gui-Xin Shi, Wei-Qiang Zhang, Guan-Bo Wang, Jing Zhao, Shu-Zhou Chai and Ze-Yu Zhao

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:27

    Content type: Research

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  23. Lately, the self-attention mechanism has marked a new milestone in the field of automatic speech recognition (ASR). Nevertheless, its performance is susceptible to environmental intrusions as the system predic...

    Authors: Lujun Li, Yikai Kang, Yuchen Shi, Ludwig Kürzinger, Tobias Watzel and Gerhard Rigoll

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:26

    Content type: Research

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  24. Due to the ad hoc nature of wireless acoustic sensor networks, the position of the sensor nodes is typically unknown. This contribution proposes a technique to estimate the position and orientation of the sens...

    Authors: Tobias Gburrek, Joerg Schmalenstroeer and Reinhold Haeb-Umbach

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:25

    Content type: Methodology

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  25. Estimating time-frequency domain masks for single-channel speech enhancement using deep learning methods has recently become a popular research field with promising results. In this paper, we propose a novel comp...

    Authors: Ziyi Xu, Samy Elshamy, Ziyue Zhao and Tim Fingscheidt

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:24

    Content type: Research

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  26. Multiple sound source localization is a hot issue of concern in recent years. The Single Source Zone (SSZ) based localization methods achieve good performance due to the detection and utilization of the Time-F...

    Authors: Maoshen Jia, Shang Gao and Changchun Bao

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:23

    Content type: Research

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  27. In this paper, we propose a novel feature compensation algorithm based on independent noise estimation, which employs a Gaussian mixture model (GMM) with fewer Gaussian components to rapidly estimate the noise...

    Authors: Yong Lü, Han Lin, Pingping Wu and Yitao Chen

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:22

    Content type: Research

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  28. When designing closed-loop electro-acoustic systems, which can commonly be found in hearing aids or public address systems, the most challenging task is canceling and/or suppressing the feedback caused by the ...

    Authors: Marco Gimm, Philipp Bulling and Gerhard Schmidt

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:21

    Content type: Research

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  29. Recently, the non-intrusive speech quality assessment method has attracted a lot of attention since it does not require the original reference signals. At the same time, neural networks began to be applied to ...

    Authors: Miao Liu, Jing Wang, Weiming Yi and Fang Liu

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:20

    Content type: Research

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  30. Sound event detection (SED), which is typically treated as a supervised problem, aims at detecting types of sound events and corresponding temporal information. It requires to estimate onset and offset annotat...

    Authors: Sichen Liu, Feiran Yang, Yin Cao and Jun Yang

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:19

    Content type: Research

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  31. Amongst the various characteristics of a speech signal, the expression of emotion is one of the characteristics that exhibits the slowest temporal dynamics. Hence, a performant speech emotion recognition (SER)...

    Authors: Duowei Tang, Peter Kuppens, Luc Geurts and Toon van Waterschoot

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:18

    Content type: Research

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  32. Deep learning-based speech enhancement algorithms have shown their powerful ability in removing both stationary and non-stationary noise components from noisy speech observations. But they often introduce arti...

    Authors: Yuxuan Ke, Andong Li, Chengshi Zheng, Renhua Peng and Xiaodong Li

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:17

    Content type: Research

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  33. In this study, we present a deep neural network-based online multi-speaker localization algorithm based on a multi-microphone array. Following the W-disjoint orthogonality principle in the spectral domain, tim...

    Authors: Hodaya Hammer, Shlomo E. Chazan, Jacob Goldberger and Sharon Gannot

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:16

    Content type: Research

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  34. An amendment to this paper has been published and can be accessed via the original article.

    Authors: Randall Ali, Toon van Waterschoot and Marc Moonen

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:15

    Content type: Correction

    Published on:

    The original article was published in EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:10

  35. Estimating the direction-of-arrival (DOA) of multiple acoustic sources is one of the key technologies for humanoid robots and drones. However, it is a most challenging problem due to a number of factors, inclu...

    Authors: Zonglong Bai, Liming Shi, Jesper Rindom Jensen, Jinwei Sun and Mads Græsbøll Christensen

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:14

    Content type: Research

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  36. Localization of multiple speakers using microphone arrays remains a challenging problem, especially in the presence of noise and reverberation. State-of-the-art localization algorithms generally exploit the sp...

    Authors: Sushmita Thakallapalli, Suryakanth V. Gangashetty and Nilesh Madhu

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:13

    Content type: Research

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  37. There has been little work in the literature on the speaker diarization of meetings with multiple distance microphones since the publications in 2012 related to the last National Institute of Standards (NIST) ...

    Authors: Beatriz Martínez-González, José M. Pardo, José A. Vallejo-Pinto, Rubén San-Segundo and Javier Ferreiros

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:12

    Content type: Research

    Published on:

  38. Nowadays automatic speech recognition (ASR) systems can achieve higher and higher accuracy rates depending on the methodology applied and datasets used. The rate decreases significantly when the ASR system is ...

    Authors: Kacper Radzikowski, Le Wang, Osamu Yoshie and Robert Nowak

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:11

    Content type: Research

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  39. An integrated version of the minimum variance distortionless response (MVDR) beamformer for speech enhancement using a microphone array has been recently developed, which merges the benefits of imposing constr...

    Authors: Randall Ali, Toon van Waterschoot and Marc Moonen

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:10

    Content type: Research

    Published on:

    The Correction to this article has been published in EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:15

  40. The presence of degradations in speech signals, which causes acoustic mismatch between training and operating conditions, deteriorates the performance of many speech-based systems. A variety of enhancement tec...

    Authors: Yuki Saishu, Amir Hossein Poorjam and Mads Græsbøll Christensen

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:9

    Content type: Research

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  41. This paper reviews recent research works in infant cry signal analysis and classification tasks. A broad range of literatures are reviewed mainly from the aspects of data acquisition, cross domain signal proce...

    Authors: Chunyan Ji, Thosini Bamunu Mudiyanselage, Yutong Gao and Yi Pan

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:8

    Content type: Review

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  42. Over the recent years, machine learning techniques have been employed to produce state-of-the-art results in several audio related tasks. The success of these approaches has been largely due to access to large...

    Authors: Rajat Hebbar, Pavlos Papadopoulos, Ramon Reyes, Alexander F. Danvers, Angelina J. Polsinelli, Suzanne A. Moseley, David A. Sbarra, Matthias R. Mehl and Shrikanth Narayanan

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:7

    Content type: Research

    Published on:

  43. We propose an algorithm for the blind separation of single-channel audio signals. It is based on a parametric model that describes the spectral properties of the sounds of musical instruments independently of ...

    Authors: Sören Schulze and Emily J. King

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:6

    Content type: Research

    Published on:

  44. Two novel methods for speaker separation of multi-microphone recordings that can also detect speakers with infrequent activity are presented. The proposed methods are based on a statistical model of the probab...

    Authors: Bracha Laufer-Goldshtein, Ronen Talmon and Sharon Gannot

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:5

    Content type: Research

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  45. We propose a method of dynamically registering out-of-vocabulary (OOV) words by assigning the pronunciations of these words to pre-inserted OOV tokens, editing the pronunciations of the tokens. To do this, we ...

    Authors: Norihide Kitaoka, Bohan Chen and Yuya Obashi

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:4

    Content type: Research

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  46. Instrumentalplaying techniques such as vibratos, glissandos, and trills often denote musical expressivity, both in classical and folk contexts. However, most existing approaches to music similarity retrieval f...

    Authors: Vincent Lostanlen, Christian El-Hajj, Mathias Rossignol, Grégoire Lafay, Joakim Andén and Mathieu Lagrange

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:3

    Content type: Research

    Published on:

  47. In this paper, a study addressing the task of tracking multiple concurrent speakers in reverberant conditions is presented. Since both past and future observations can contribute to the current location estima...

    Authors: Yuval Dorfan, Boaz Schwartz and Sharon Gannot

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:2

    Content type: Research

    Published on:

  48. The progressive paradigm is a promising strategy to optimize network performance for speech enhancement purposes. Recent works have shown different strategies to improve the accuracy of speech enhancement solu...

    Authors: Jorge Llombart, Dayana Ribas, Antonio Miguel, Luis Vicente, Alfonso Ortega and Eduardo Lleida

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2021 2021:1

    Content type: Research

    Published on:

  49. In real applications, environmental effects such as additive noise and room reverberation lead to a mismatch between training and testing signals that substantially reduces the performance of far-field speaker...

    Authors: Masoud Geravanchizadeh and Sina Ghalamiosgouei

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2020 2020:20

    Content type: Research

    Published on:

  50. In this paper, we investigate the performance of two deep learning paradigms for the audio-based tasks of acoustic scene, environmental sound and domestic activity classification. In particular, a convolutiona...

    Authors: Shahin Amiriparian, Maurice Gerczuk, Sandra Ottl, Lukas Stappen, Alice Baird, Lukas Koebe and Björn Schuller

    Citation: EURASIP Journal on Audio, Speech, and Music Processing 2020 2020:19

    Content type: Research

    Published on:

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  • ISSN: 1687-4722 (electronic)