On the quality assessment of sound signals

Lima, Amaro A. de; Freeland, Fabio P.; Jesus, Rafael A. de; Bispo, Bruno; Biscainho, Luiz W. P.; Netto, Sérgio L.; Said, Amir; Kalker, A.A.C.M.; Schafer, Ronald W.; Lee, B.; Jam, Mehrban

doi:10.1109/iscas.2008.4541443

Cited by 17 publications

(8 citation statements)

References 2 publications

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“…The implementation of PEAQ [18] [56] is the basic version using the MATLAB computer code from Kabal [57], which has been shown to agree very closely with the ITU standard [58]. The basic version of PEAQ constructs an auditory model using short-time FFTs of a signal sampled at 48 kHz and divided into 2048-sample (43 ms) overlapping segments.…”

Section: Resultsmentioning

confidence: 99%

The Hearing-Aid Audio Quality Index (HAAQI)

Kates

Arehart

2016

IEEE/ACM Trans. Audio Speech Lang. Process.

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This paper presents an index designed to predict music quality for individuals listening through hearing aids. The index is “intrusive”, that is, it compares the degraded signal being evaluated to a reference signal. The index is based on a model of the auditory periphery that includes the effects of hearing loss. Outputs from the auditory model are used to measure changes in the signal time-frequency envelope modulation, temporal fine structure, and long-term spectrum caused by the hearing aid processing. The index is constructed by combining a term sensitive to noise and nonlinear distortion with a second term sensitive to changes in the long-term spectrum. The index is fitted to an existing database of music quality judgments made by listeners having normal or impaired hearing. The data comprise ratings for three music excerpts (classical orchestra, jazz trio, and jazz singer), each processed through 100 conditions representative of hearing-aid processing and listening situations. The overall accuracy of the index is high, with a correlation coefficient of 0.970 when computed over all of the processing conditions and averaged over the combined groups of listeners having normal and impaired hearing.

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Section: Resultsmentioning

confidence: 99%

The Hearing-Aid Audio Quality Index (HAAQI)

Kates

Arehart

2016

IEEE/ACM Trans. Audio Speech Lang. Process.

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“…3) W-PESQ: O W-PESQ (Wideband Perceptual Evaluation of Speech Quality)é um algoritmo para avaliação objetiva da qualidade de sinais de fala de banda larga (amostrados a 16 kHz) [10]- [12]. Ele utiliza as versões de referência (original) e degradada (processada) de um sinal de fala para avaliar objetivamente a degradação perceptual daúltima, qué e quantificada na escala 1-5 de opinião média (Mean Opinion Score -MOS) de acordo com a classificação da categoria de degradação (Degradation Category Rating -DCR), resultando na pontuação MOS-LQO (MOS-Listening Quality Objetive).…”

Section: Sistema De Oclusãounclassified

Método cepstral para estimação da resposta ao impulso do efeito de oclusão em sistemas de auxílio à audição

Bispo¹,

Borges²,

Costa³

2019

Anais De XXXVII Simpósio Brasileiro De Telecomunicações E Processamento De Sinais

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Resumo-O efeito de oclusãoé uma queixa comum de usuários de aparelhos auditivos que utilizam moldes sem ventilação ou com ventilação estreita, os quais promovem uma sensação de abafamento da própria voz. Na literatura, controladores fixos e adaptativos têm sido propostos para a redução desse efeito, o qual possui uma soluçãoótima não-causal. Este trabalho propõe um método cepstral para identificar a resposta ao impulso da oclusão e um sistema de controle fixo que utiliza essa estimativa para redução do efeito de oclusão em sistemas de auxílioà audição. Simulações indicam que a eficiência do método cepstral depende do tamanho da janela de análise, resultando em estimativas com desalinhamento média de-28,77 dB para janelas de análise de 2 s. E que o controlador aproxima o sinal a ser ouvido pelo usuário do seu valor ideal, diminuindo em 0,34 dB a potência do erro e aumentando em 0,12 MOS-LQO a qualidade perceptual do sinal. Palavras-Chave-Efeito de oclusão, aparelho auditivo, análise cepstral, controle ativo.

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“…Huber and Kollmeier [13] proposed a novel audio quality assessment method and extended the range of distortions on speech and music signals. More work is summarized in [4,7,32].…”

Section: Related Workmentioning

confidence: 99%

“…However, the ultimate goal of all the work mentioned above was to develop, test, or compare multimedia devices, codecs and networks for high-end audio or video services (e.g., VoIP and telepresence services) [4,7,32]. Moreover, both the reference signal and the distorted signal processed by the test system were available and generally well aligned.…”

Section: Related Workmentioning

confidence: 99%

Non-reference audio quality assessment for online live music recordings

Wang

Cai

et al. 2013

Proceedings of the 21st ACM International Conference on Multimedia

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Immensely popular video sharing websites such as YouTube have become the most important sources of music information for Internet users and the most prominent platform for sharing live music. The audio quality of this huge amount of live music recordings, however, varies significantly due to factors such as environmental noise, location, and recording device. However, most video search engines do not take audio quality into consideration when retrieving and ranking results. Given the fact that most users prefer live music videos with better audio quality, we propose the first automatic, non-reference audio quality assessment framework for live music video search online. We first construct two annotated datasets of live music recordings. The first dataset contains 500 human-annotated pieces, and the second contains 2,400 synthetic pieces systematically generated by adding noise effects to clean recordings. Then, we formulate the assessment task as a ranking problem and try to solve it using a learning-based scheme. To validate the effectiveness of our framework, we perform both objective and subjective evaluations. Results show that our framework significantly improves the ranking performance of live music recording retrieval and can prove useful for various real-world music applications.

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On the quality assessment of sound signals

Cited by 17 publications

References 2 publications

The Hearing-Aid Audio Quality Index (HAAQI)

The Hearing-Aid Audio Quality Index (HAAQI)

Método cepstral para estimação da resposta ao impulso do efeito de oclusão em sistemas de auxílio à audição

Non-reference audio quality assessment for online live music recordings

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