The relationship of voice onset time and Voice Offset Time to physical age

Singh, Rita; Keshet, Joseph; Gençağa, Deniz; Raj, Bhiksha

doi:10.1109/icassp.2016.7472707

Cited by 12 publications

(9 citation statements)

References 23 publications

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“…It seems to suggest that cues in speech for MSSS are partly asymmetric. It has been found that voice onset time (VOT) is a predictive cue for postaspiration [Klatt, 1975, Lisker andAbramson, 1967], while similar conclusions have been drawn for voice offset time (VoffT) [Singh et al, 2016b, Pind, 1996. Furthermore, it has also been observed that there is an acoustical asymmetry in vowel production [Patel et al, 2017].…”

Section: Forward and Backward Resetmentioning

confidence: 78%

Analysis of memory in LSTM-RNNs for source separation

Zegers,

Van hamme

2020

Preprint

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Long short-term memory recurrent neural networks (LSTM-RNNs) are considered state-of-the art in many speech processing tasks. The recurrence in the network, in principle, allows any input to be remembered for an indefinite time, a feature very useful for sequential data like speech. However, very little is known about which information is actually stored in the LSTM and for how long. We address this problem by using a memory reset approach which allows us to evaluate network performance depending on the allowed memory time span. We apply this approach to the task of multi-speaker source separation, but it can be used for any task using RNNs. We find a strong performance effect of shortterm (shorter than 100 milliseconds) linguistic processes. Only speaker characteristics are kept in the memory for longer than 400 milliseconds. Furthermore, we confirm that performance-wise it is sufficient to implement longer memory in deeper layers. Finally, in a bidirectional model, the back-ward models contributes slightly more to the separation performance than the forward model.

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Section: Forward and Backward Resetmentioning

confidence: 78%

Analysis of memory in LSTM-RNNs for source separation

Zegers,

Van hamme

2020

Preprint

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“…In a speech signal, Voice Onset Time (VOT) was the period between the release of a plosive and the onset of vocal cord vibrations in the production of the following sound. Voice Offset Time (VOFT), on the other hand, was the period between the end of a voiced sound and the release of the following plosive [3]. Cases such as threatening calls, false alarms, kidnapping calls can be solved with the identifying voice of a person.…”

Section: ) Speech or Voice Examinationmentioning

confidence: 99%

Features and Methods of Human Age Estimation: Opportunities and Challenges in Medical Image Processing

Patil¹

2021

TURCOMAT

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Age estimation of living species is an open and interesting problem due to its medico-legal importance and humans are no exception to this. Human body undergoes various physiological changes such as facial wrinkles, walking habits. Besides this, biological changes also help in human age estimation. Some of the changes are body skeleton and craniofacial growth. Various age estimation methods viz. manual, semi-automated and automated methods are available. Each of these methods has their merits and demerits. The popular manual and semi-automated age estimation methods are prone to human observation error and need sophisticated equipments. The advent of computational methods has opened new possibilities towards automation of the problem. Hence there is growing interest in fully automated methods. Through this paper, we have discussed different aspects of human age estimation and presented a brief review of various available methods.

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“…Speech signals convey a speaker's important information such as age, gender, body size, emotional state, and health state [12][13][14][15][16] . The physiological effects of cigarette smoking have been well-documented [17][18][19] and include pharyngeal diseases and disorders resulting from prolonged effects of a variety of harmful chemicals in the cigarette smoke.…”

Section: Introductionmentioning

confidence: 99%

Towards the Objective Speech Assessment of Smoking Status based on Voice Features: A Review of the Literature

Bullen

Chu

et al. 2023

Journal of Voice

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Background and Objective: In smoking cessation clinical research and practice, objective validation of self-reported smoking status is crucial for ensuring the reliability of the primary outcome, that is, smoking abstinence. Speech signals convey important information about a speaker, such as age, gender, body size, emotional state, and health state. We investigated (1) if smoking could measurably alter voice features, (2) if smoking cessation could lead to changes in voice, and therefore (3) if the voice-based smoking status assessment has the potential to be used as an objective smoking cessation validation method.Methods: A systematic review of the scientific literature was conducted to compile studies on smoking status assessment based on voice features. We searched nine scientific databases for original studies involving the effects of smoking on voice features, the effects of smoking cessation on voice features.Results: A total of 34 studies were identified for review. We found that fundamental frequency, jitter, shimmer, harmonics to noise ratio, and other voice features are affected by smoking and could be used to assess smoking status. Conclusion:Speech assessment of smoking status based on voice features has potential as a smoking status validation method, as it is simple, reliable, and less time-consuming. Furthermore, this study provides recommendations for future research on the objective speech assessment of smoking status based on voice features.

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The relationship of voice onset time and Voice Offset Time to physical age

Cited by 12 publications

References 23 publications

Analysis of memory in LSTM-RNNs for source separation

Analysis of memory in LSTM-RNNs for source separation

Features and Methods of Human Age Estimation: Opportunities and Challenges in Medical Image Processing

Towards the Objective Speech Assessment of Smoking Status based on Voice Features: A Review of the Literature

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