Page 1 of 11
End-to-end speech to text translation aims to directly translate speech from one language into text in another, posing a challenging cross-modal task particularly in scenarios of limited data. Multi-task learn...
While deep learning technologies have made remarkable progress in generating deepfakes, their misuse has become a well-known concern. As a result, the ubiquitous usage of deepfakes for increasing false informa...
Polyphonic sound source localization and detection (SSLD) task aims to recognize the categories of sound events, identify their onset and offset times, and detect their corresponding direction-of-arrival (DOA)...
Dysarthria is a speech disorder that affects the ability to communicate due to articulation difficulties. This research proposes a novel method for automatic dysarthria detection (ADD) and automatic dysarthria...
This work introduces a large dataset comprising impulse responses of spatially distributed sources within a plane parallel to a planar microphone array. The dataset, named MIRACLE, encompasses 856,128 single-c...
A new method for estimating the first and second derivatives of discrete audio signals intended to achieve higher computational precision in analyzing the performance and characteristics of digital audio syste...
Time signature detection is a fundamental task in music information retrieval, aiding in music organization. In recent years, the demand for robust and efficient methods in music analysis has amplified, unders...
Limited data availability remains a significant challenge for Whisper’s low-resource speech recognition performance, falling short of practical application requirements. While previous studies have successfull...
In the era of advanced text-to-speech (TTS) systems capable of generating high-fidelity, human-like speech by referring a reference speech, voice cloning (VC), or zero-shot TTS (ZS-TTS), stands out as an impor...
Selective attention is a crucial ability of the auditory system. Computationally, following an auditory object can be illustrated as tracking its acoustic properties, e.g., pitch, timbre, or location in space....
This work studies neural modeling of nonlinear parametric audio circuits, focusing on how the diversity of settings of the target device user controls seen during training affects network generalization. To st...
Visual speech recognition (VSR) is a challenging task that has received increasing interest during the last few decades. Current state of the art employs powerful end-to-end architectures based on deep learnin...
This article introduces Mi-Go, a tool aimed at evaluating the performance and adaptability of general-purpose speech recognition machine learning models across diverse real-world scenarios. The tool leverages ...
Dynamic parameterization of acoustic environments has drawn widespread attention in the field of audio processing. Precise representation of local room acoustic characteristics is crucial when designing audio ...
In robotics, echolocation has been used to detect acoustic reflectors, e.g., walls, as it aids the robotic platform to navigate in darkness and also helps detect transparent surfaces. However, the transfer fun...
The original article was published in EURASIP Journal on Audio, Speech, and Music Processing 2024 2024:18
Speech signals are often distorted by reverberation and noise, with a widely distributed signal-to-noise ratio (SNR). To address this, our study develops robust, deep neural network (DNN)-based speech enhancem...
Technologies in healthcare, smart homes, security, ecology, and entertainment all deploy audio event detection (AED) in order to detect sound events in an audio recording. Effective AED techniques rely heavily...
Spoofed speeches are becoming a big threat to society due to advancements in artificial intelligence techniques. Therefore, there must be an automated spoofing detector that can be integrated into automatic sp...
The Correction to this article has been published in EURASIP Journal on Audio, Speech, and Music Processing 2024 2024:21
Most soundfield synthesis approaches deal with extensive and regular loudspeaker arrays, which are often not suitable for home audio systems, due to physical space constraints. In this article, we propose a te...
Audio augmented reality (AAR), a prominent topic in the field of audio, requires understanding the listening environment of the user for rendering an authentic virtual auditory object. Reverberation time (
The vast amount of information stored in audio repositories makes necessary the development of efficient and automatic methods to search on audio content. In that direction, search on speech (SoS) has received...
Analyzing songs is a problem that is being investigated to aid various operations on music access platforms. At the beginning of these problems is the identification of the person who sings the song. In this s...
Accurately representing the sound field with high spatial resolution is crucial for immersive and interactive sound field reproduction technology. In recent studies, there has been a notable emphasis on effici...
This work constitutes the first approach for automatically classifying the surface that the voiding flow impacts in non-invasive sound uroflowmetry tests using machine learning. Often, the voiding flow impacts...
Speech synthesis has made significant strides thanks to the transition from machine learning to deep learning models. Contemporary text-to-speech (TTS) models possess the capability to generate speech of excep...
Claimed identities of speakers can be verified by means of automatic speaker verification (ASV) systems, also known as voice biometric systems. Focusing on security and robustness against spoofing attacks on A...
Audio effects are an ubiquitous tool in music production due to the interesting ways in which they can shape the sound of music. Guitar effects, the subset of all audio effects focusing on guitar signals, are ...
Recent advancements in deep learning-based speech enhancement models have extensively used attention mechanisms to achieve state-of-the-art methods by demonstrating their effectiveness. This paper proposes a t...
Chinese traditional music, a vital expression of Chinese cultural heritage, possesses both a profound emotional resonance and artistic allure. This study sets forth to refine and analyze the acoustical feature...
Speech coding is a method to reduce the amount of data needs to represent speech signals by exploiting the statistical properties of the speech signal. Recently, in the speech coding process, a neural network ...
The original article was published in EURASIP Journal on Audio, Speech, and Music Processing 2023 2023:46
Melody harmonization, which involves generating a chord progression that complements a user-provided melody, continues to pose a significant challenge. A chord progression must not only be in harmony with the ...
Musical instrument sound synthesis (MISS) often utilizes a text-to-speech framework because of its similarity to speech in terms of generating sounds from symbols. Moreover, a plucked string instrument, such a...
Shouted and normal speech classification plays an important role in many speech-related applications. The existing works are often based on magnitude-based features and ignore phase-based features, which are d...
Acoustic scene classification (ASC) is the process of identifying the acoustic environment or scene from which an audio signal is recorded. In this work, we propose an encoder-decoder-based approach to ASC, wh...
Acoustic sensing by multiple devices connected in a wireless acoustic sensor network (WASN) creates new opportunities for multichannel signal processing. However, the autonomy of agents in such a network still...
Target speaker separation aims to separate the speech components of the target speaker from mixed speech and remove extraneous components such as noise. In recent years, deep learning-based speech separation m...
Musical score rearrangement is an emerging area in symbolic music processing, which aims to transform a musical score into a different style. This study focuses on the task of changing the playing difficulty o...
The task of bandwidth extension addresses the generation of missing high frequencies of audio signals based on knowledge of the low-frequency part of the sound. This task applies to various problems, such as a...
This study focuses on exploring the acoustic differences between synthesized Guzheng pieces and real Guzheng performances, with the aim of improving the quality of synthesized Guzheng music. A dataset with con...
Predominant source separation is the separation of one or more desired predominant signals, such as voice or leading instruments, from polyphonic music. The proposed work uses time-frequency filtering on predo...
Speakers with dysarthria often struggle to accurately pronounce words and effectively communicate with others. Automatic speech recognition (ASR) is a powerful tool for extracting the content from speakers wit...
This article presents the research work on improving speech recognition systems for the morphologically complex Malayalam language using subword tokens for language modeling. The speech recognition system is b...
Speaker embeddings, from the ECAPA-TDNN speaker verification network, were recently introduced as features for the task of clustering microphones in ad hoc arrays. Our previous work demonstrated that, in compa...
The Correction to this article has been published in EURASIP Journal on Audio, Speech, and Music Processing 2024 2024:5
Non-parallel data voice conversion (VC) has achieved considerable breakthroughs due to self-supervised pre-trained representation (SSPR) being used in recent years. Features extracted by the pre-trained model ...
Appropriate background music in e-commerce advertisements can help stimulate consumption and build product image. However, many factors like emotion and product category should be taken into account, which mak...
Snoring affects 57 % of men, 40 % of women, and 27 % of children in the USA. Besides, snoring is highly correlated with obstructive sleep apnoea (OSA), which is characterised by loud and frequent snoring. OSA ...
Unsupervised anomalous sound detection (ASD) aims to detect unknown anomalous sounds of devices when only normal sound data is available. The autoencoder (AE) and self-supervised learning based methods are two...
Learn more about the impact the EURASIP Journal on Audio, Speech, and Music Processing has worldwide
Citation Impact 2023
Journal Impact Factor: 1.7
5-year Journal Impact Factor: 1.6
Source Normalized Impact per Paper (SNIP): 1.051
SCImago Journal Rank (SJR): 0.414
Speed 2023
Submission to first editorial decision (median days): 17
Submission to acceptance (median days): 154
Usage 2023
Downloads: 368,607
Altmetric mentions: 70
