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Speaker recognition

About: Speaker recognition is a research topic. Over the lifetime, 14990 publications have been published within this topic receiving 310061 citations.


Papers
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Journal ArticleDOI
TL;DR: Functional neuroimaging reveals that in the context of speaker recognition, the assessment of person familiarity does not necessarily engage supra-modal cortical substrates but can result from the direct sharing of information between auditory voice and visual face regions.
Abstract: Face and voice processing contribute to person recognition, but it remains unclear how the segregated specialized cortical modules interact. Using functional neuroimaging, we observed cross-modal responses to voices of familiar persons in the fusiform face area, as localized separately using visual stimuli. Voices of familiar persons only activated the face area during a task that emphasized speaker recognition over recognition of verbal content. Analyses of functional connectivity between cortical territories show that the fusiform face region is coupled with the superior temporal sulcus voice region during familiar speaker recognition, but not with any of the other cortical regions normally active in person recognition or in other tasks involving voices. These findings are relevant for models of the cognitive processes and neural circuitry involved in speaker recognition. They reveal that in the context of speaker recognition, the assessment of person familiarity does not necessarily engage supramodal cortical substrates but can result from the direct sharing of information between auditory voice and visual face regions.

310 citations

Proceedings ArticleDOI
12 May 2019
TL;DR: This paper proposes a powerful speaker recognition deep network, using a ‘thin-ResNet’ trunk architecture, and a dictionary-based NetVLAD or GhostVLAD layer to aggregate features across time, that can be trained end-to-end.
Abstract: The objective of this paper is speaker recognition ‘in the wild’ – where utterances may be of variable length and also contain irrelevant signals. Crucial elements in the design of deep networks for this task are the type of trunk (frame level) network, and the method of temporal aggregation. We propose a powerful speaker recognition deep network, using a ‘thin-ResNet’ trunk architecture, and a dictionary-based NetVLAD or GhostVLAD layer to aggregate features across time, that can be trained end-to-end. We show that our network achieves state of the art performance by a significant margin on the VoxCeleb1 test set for speaker recognition, whilst requiring fewer parameters than previous methods. We also investigate the effect of utterance length on performance, and conclude that for ‘in the wild’ data, a longer length is beneficial.

308 citations

Journal ArticleDOI
TL;DR: This article found that the right superior temporal sulcus (STS) is involved in processing the human voice and showed that it functionally cooperates with the left superior temporal cortex (LSTM) during speaker recognition.

306 citations

Proceedings ArticleDOI
01 May 1999
TL;DR: Details of the kinds of usability and system design problems likely in current systems and several common patterns of error correction that are found are presented.
Abstract: A study was conducted to evaluate user performance and satisfaction in completion of a set of text creation tasks using three commercially available continuous speech recognition systems. The study also compared user performance on similar tasks using keyboard input. One part of the study (Initial Use) involved 24 users who enrolled, received training and carried out practice tasks, and then completed a set of transcription and composition tasks in a single session. In a parallel effort (Extended Use), four researchers used speech recognition to carry out real work tasks over 10 sessions with each of the three speech recognition software products. This paper presents results from the Initial Use phase of the study along with some preliminary results from the Extended Use phase. We present details of the kinds of usability and system design problems likely in current systems and several common patterns of error correction that we found.

304 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023165
2022468
2021283
2020475
2019484
2018420