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A method called joint connectionist temporal classification (CTC)-attention-based speech recognition has recently received increasing focus and has achieved impressive performance. A hybrid end-to-end architec...
Voice conversion (VC) is a technique of exclusively converting speaker-specific information in the source speech while preserving the associated phonemic information. Non-negative matrix factorization (NMF)-ba...
Search on speech (SoS) is a challenging area due to the huge amount of information stored in audio and video repositories. Spoken term detection (STD) is an SoS-related task aiming to retrieve data from a spee...
Voice-enabled interaction systems in domestic environments have attracted significant interest recently, being the focus of smart home research projects and commercial voice assistant home devices. Within the ...
Speech emotion recognition methods combining articulatory information with acoustic features have been previously shown to improve recognition performance. Collection of articulatory data on a large scale may ...
The huge amount of information stored in audio and video repositories makes search on speech (SoS) a priority area nowadays. Within SoS, Query-by-Example Spoken Term Detection (QbE STD) aims to retrieve data f...
In this paper, we apply a latent class model (LCM) to the task of speaker diarization. LCM is similar to Patrick Kenny’s variational Bayes (VB) method in that it uses soft information and avoids premature hard...
We propose a new method for music detection from broadcasting contents using the convolutional neural networks with a Mel-scale kernel. In this detection task, music segments should be annotated from the broad...
Singing voice analysis has been a topic of research to assist several applications in the domain of music information retrieval system. One such major area is singer identification (SID). There has been enormo...
Audio signals represent a wide diversity of acoustic events, from background environmental noise to spoken communication. Machine learning models such as neural networks have already been proposed for audio si...
There are many studies on detecting human speech from artificially generated speech and automatic speaker verification (ASV) that aim to detect and identify whether the given speech belongs to a given speaker....
In this paper, an adaptive averaging a priori SNR estimation employing critical band processing is proposed. The proposed method modifies the current decision-directed a priori SNR estimation to achieve faster...
Dynamic time warping (DTW) can be used to compute the similarity between two sequences of generally differing length. We propose a modification to DTW that performs individual and independent pairwise alignmen...
In response to renewed interest in virtual and augmented reality, the need for high-quality spatial audio systems has emerged. The reproduction of immersive and realistic virtual sound requires high resolution...
This paper proposes two novel linguistic features extracted from text input for prosody generation in a Mandarin text-to-speech system. The first feature is the punctuation confidence (PC), which measures the ...
Current automatic speech recognition (ASR) systems achieve over 90–95% accuracy, depending on the methodology applied and datasets used. However, the level of accuracy decreases significantly when the same ASR...
The overall recognition rate will reduce due to the increase of emotional confusion in multiple speech emotion recognition. To solve the problem, we propose a speech emotion recognition method based on the dec...
Filter banks on spectrums play an important role in many audio applications. Traditionally, the filters are linearly distributed on perceptual frequency scale such as Mel scale. To make the output smoother, th...
This paper deals with a project of Automatic Bird Species Recognition Based on Bird Vocalization. Eighteen bird species of 6 different families were analyzed. At first, human factor cepstral coefficients repre...
A transfer learning-based end-to-end speech recognition approach is presented in two levels in our framework. Firstly, a feature extraction approach combining multilingual deep neural network (DNN) training wi...
In this paper, a web-based spoken dialog generation environment which enables users to edit dialogs with a video virtual assistant is developed and to also select the 3D motions and tone of voice for the assis...
In this paper, a robust and highly imperceptible audio watermarking technique is presented based on discrete cosine transform (DCT) and singular value decomposition (SVD). The low-frequency components of the a...
The emerging field of computational acoustic monitoring aims at retrieving high-level information from acoustic scenes recorded by some network of sensors. These networks gather large amounts of data requiring...
Several factors contribute to the performance of speaker diarization systems. For instance, the appropriate selection of speech features is one of the key aspects that affect speaker diarization systems. The o...
We present the open-source implementation of the first fully automatic and comprehensive DJ system, able to generate seamless music mixes using songs from a given library much like a human DJ does.
Recently, sound recognition has been used to identify sounds, such as the sound of a car, or a river. However, sounds have nuances that may be better described by adjective-noun pairs such as “slow car” and ve...
As the foundation of many applications, multipitch estimation problem has always been the focus of acoustic music processing; however, existing algorithms perform deficiently due to its complexity. In this pap...
Voice activity detection (VAD) is an important preprocessing step for various speech applications to identify speech and non-speech periods in input signals. In this paper, we propose a deep neural network (DN...
The performance of automatic speech recognition systems degrades in the presence of emotional states and in adverse environments (e.g., noisy conditions). This greatly limits the deployment of speech recogniti...
The successful treatment of hearing loss depends on the individual practitioner’s experience and skill. So far, there is no standard available to evaluate the practitioner’s testing skills. To assess every pra...
This work studies a wind noise reduction approach for communication applications in a car environment. An endfire array consisting of two microphones is considered as a substitute for an ordinary cardioid micr...
Recurrent neural networks (RNNs) have shown an ability to model temporal dependencies. However, the problem of exploding or vanishing gradients has limited their application. In recent years, long short-term m...
In this paper, a novel parametric prosody coding approach for Mandarin speech is proposed. It employs a hierarchical prosodic model (HPM) as a prosody-generating model in the encoder to analyze the speech pros...
Filter banks on short-time Fourier transform (STFT) spectrogram have long been studied to analyze and process audios. The frameshift in STFT procedure determines the temporal resolution. However, in many discr...
The speech intelligibility of indoor public address systems is degraded by reverberation and background noise. This paper proposes a preprocessing method that combines speech enhancement and inverse filtering ...
Query-by-example Spoken Term Detection (QbE STD) aims to retrieve data from a speech repository given an acoustic (spoken) query containing the term of interest as the input. This paper presents the systems su...
Automatic extraction of acoustic regions of interest from recordings captured in realistic clinical environments is a necessary preprocessing step in any cry analysis system. In this study, we propose a hidden...
Audio signals are a type of high-dimensional data, and their clustering is critical. However, distance calculation failures, inefficient index trees, and cluster overlaps, derived from the equidistance, redund...
In speech enhancement, noise power spectral density (PSD) estimation plays a key role in determining appropriate de-nosing gains. In this paper, we propose a robust noise PSD estimator for binaural speech enha...
Large vocabulary continuous speech recognition (LVCSR) has naturally been demanded for transcribing daily conversations, while developing spoken text data to train LVCSR is costly and time-consuming. In this p...
Robustness against background noise is a major research area for speech-related applications such as speech recognition and speaker recognition. One of the many solutions for this problem is to detect speech-d...
Within search-on-speech, Spoken Term Detection (STD) aims to retrieve data from a speech repository given a textual representation of a search term. This paper presents an international open evaluation for sea...
The task of speaker diarization is to answer the question "who spoke when?" In this paper, we present different clustering approaches which consist of Evolutionary Computation Algorithms (ECAs) such as Genetic...
This paper throws light on chaotic shift keying-based speech encryption and decryption method. In this method, the input speech signals are sampled and its values are segmented into four levels, namely L ...
In normal modally voiced utterances, voiceless fricatives like [s], [ʃ], [f], and [x] vary such that their aperiodic pitch impressions mirror the pitch level of the adjacent F0 contour. For instance, if the F0...
An artificial neural network is an important model for training features of voice conversion (VC) tasks. Typically, neural networks (NNs) are very effective in processing nonlinear features, such as Mel Cepstr...
Audio fingerprinting has been an active research field typically used for music identification. Robust audio fingerprinting technology is used to successfully perform content-based audio identification regardl...
In this paper, we present a voice conversion (VC) method that does not use any parallel data while training the model. Voice conversion is a technique where only speaker-specific information in the source spee...
Onset detection still has room for improvement, especially when dealing with polyphonic music signals. For certain purposes in which the correctness of the result is a must, user intervention is hence required...
Speech synthesis has been applied in many kinds of practical applications. Currently, state-of-the-art speech synthesis uses statistical methods based on hidden Markov model (HMM). Speech synthesized by statis...
Learn more about the impact the EURASIP Journal on Audio, Speech, and Music Processing has worldwide
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2.114 - 2-year Impact Factor (2021)
1.630 - 5-year Impact Factor (2021)
1.101 - Source Normalized Impact per Paper (SNIP)
0.259 - SCImago Journal Rank (SJR)
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