Contemporary Methods for Speech Parameterization

Ganchev, Todor

doi:10.1007/978-1-4419-8447-0_1

Cited by 2 publications

(2 citation statements)

References 73 publications

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“…For each segment we computed a set of 90 audio descriptors, including 35 Linear-Frequency Cepstral Coefficients (LFCC) [67] and their first and second temporal derivatives, referred to as ΔLFCC and Δ 2 LFCC respectively. Here we kept only the first 20 Δ 2 LFCCs, as the last 15 were found to be less informative.…”

Section: Methodsmentioning

confidence: 99%

Automated Sound Recognition Provides Insights into the Behavioral Ecology of a Tropical Bird

et al. 2017

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Computer-assisted species recognition facilitates the analysis of relevant biological information in continuous audio recordings. In the present study, we assess the suitability of this approach for determining distinct life-cycle phases of the Southern Lapwing Vanellus chilensis lampronotus based on adult vocal activity. For this purpose we use passive 14-min and 30-min soundscape recordings (n = 33 201) collected in 24/7 mode between November 2012 and October 2013 in Brazil’s Pantanal wetlands. Time-stamped detections of V. chilensis call events (n = 62 292) were obtained with a species-specific sound recognizer. We demonstrate that the breeding season fell in a three-month period from mid-May to early August 2013, between the end of the flood cycle and the height of the dry season. Several phases of the lapwing’s life history were identified with presumed error margins of a few days: pre-breeding, territory establishment and egg-laying, incubation, hatching, parental defense of chicks, and post-breeding. Diurnal time budgets confirm high acoustic activity levels during midday hours in June and July, indicative of adults defending young. By August, activity patterns had reverted to nonbreeding mode, with peaks around dawn and dusk and low call frequency during midday heat. We assess the current technological limitations of the V. chilensis recognizer through a comprehensive performance assessment and scrutinize the usefulness of automated acoustic recognizers in studies on the distribution pattern, ecology, life history, and conservation status of sound-producing animal species.

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Section: Methodsmentioning

confidence: 99%

Automated Sound Recognition Provides Insights into the Behavioral Ecology of a Tropical Bird

et al. 2017

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“…The outputs of the filter bank are compressed by the logarithm function. Finally, the Discrete Cosine Transform (DCT) is used to decorrelate the obtained outputs, yielding the HFCC Coefficients (Ganchev, 2011):…”

Section: Human Factor Cepstral Coefficient (Hfcc)mentioning

confidence: 99%

Recognition of Pathological Voices by Human Factor Cepstral Coefficients (HFCC)

Hamdi¹,

Hajji²,

Cherif³

2020

Journal of Computer Science

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Human speech is a means of communication that is very important in our daily lives. It is characterized by its great ability to transmit our ideas, our emotions, our personality etc. So, any alteration of the voice can prevent the person from exercising his professional and daily life naturally. It is for these reasons that it is very necessary to implement systems for detecting and classifying vocal pathologies. These automatic systems can help clinicians customize and detect the existence of any vocal pathology. In this context, several tools have been introduced to achieve early detection of voice disorders. Among these tools are the Human Factor Cepstral Coefficients (HFCC) combined with prosodic parameters, the Noise-Harmonic Ratio (NHR), the Harmonic-Noise Ratio (HNR), analysis of trend Fluctuations (DFA) and Fundamental frequency (F0). These parameters are introduced and calculated in every frame. In this study, we used a variation of HFCC called Equivalent Rectangular Bandwidth (ERB) to study the effects of HFCC on the classification of pathological voices. Using the HTK classifiers, the classification is carried out on two pathological databases, Massachusetts Eye and Ear Infirmary (MEEI) and Saarbruecken Voice Database (SVD). To assess the performance of the system, we used sensitivity and specificity.

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Contemporary Methods for Speech Parameterization

Cited by 2 publications

References 73 publications

Automated Sound Recognition Provides Insights into the Behavioral Ecology of a Tropical Bird

Automated Sound Recognition Provides Insights into the Behavioral Ecology of a Tropical Bird

Recognition of Pathological Voices by Human Factor Cepstral Coefficients (HFCC)

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