Usable Speech Processing: A Filterless Approach in the Presence of Interference

Smolenski, Brett Y.; Ramachandran, Ramkumar Ketti

doi:10.1109/mcas.2011.941078

Cited by 17 publications

(3 citation statements)

References 16 publications

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“…In this project, the length of each frame is 30 ms and the overlap between consecutive frames is 20 ms. Each frame is multiplied by a Hamming window and effectively represents the middle 10 ms of its entire 30 ms length. Frame selection is achieved by a voice activity detector that keeps speech-like high energy segments (usable frames [65]) and discards silence (not usable frames) [66].…”

Section: A Speaker Identification Projectmentioning

confidence: 99%

Vertical Integration of Biometrics Across the Curriculum: Case Study of Speaker, Face and Iris Recognition

Ramachandran

Dahm

Nickel

et al. 2014

IEEE Circuits Syst. Mag.

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Vertical integration is a powerful curricular tool that allows students to better appreciate the interconnections among the concepts acquired and learned in different courses. it can be used to bring a modern topic at all levels of the undergraduate curriculum with little additional resources. this paper gives a brief survey of various vertical integration efforts and describes one effort at integrating biometrics throughout the curriculum. the focus is on three senior level projects (speaker, face and iris recognition) that not only rely on vertical integration but also reinforce design, software skills and knowledge of stEm concepts. the freshman through junior levels are also described. the assessment results show that students acquire specific learning outcomes and perceive the value of vertical integration. iEEE circUits And systEms mAgAzinE third QUArtEr 2014

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Section: A Speaker Identification Projectmentioning

confidence: 99%

Vertical Integration of Biometrics Across the Curriculum: Case Study of Speaker, Face and Iris Recognition

Ramachandran

Dahm

Nickel

et al. 2014

IEEE Circuits Syst. Mag.

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“…The second approach is to detect the presence of more than one speaker at every time instance, which is mainly referred to as overlapped-speech detection [4,5,6]. In many applications, including the problem investigated in this study, the latter suffices in mitigating the degradations caused by co-channel speech (for a review see [7]). An example is reducing errors in speaker diarization by omitting overlapping speech regions [8].…”

Section: Introductionmentioning

confidence: 99%

Overlapped-speech detection with applications to driver assessment for in-vehicle active safety systems

Shokouhi

Sathyanarayana

Sadjadi

et al. 2013

2013 IEEE International Conference on Acoustics, Speech and Signal Processing

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In this study we propose a system for overlapped-speech detection. Spectral harmonicity and envelope features are extracted to represent overlapped and single-speaker speech using Gaussian mixture models (GMM). The system is shown to effectively discriminate the single and overlapped speech classes. We further increase the discrimination by proposing a phoneme selection scheme to generate more reliable artificial overlapped data for model training. Evaluations on artificially generated co-channel data show that the novelty in feature selection and phoneme omission results in a relative improvement of 10% in the detection accuracy compared to baseline. As an example application, we evaluate the effectiveness of overlapped-speech detection for vehicular environments and its potential in assessing driver alertness. Results indicate a good correlation between driver performance and the amount and location of overlapped-speech segments.

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“…Since additive noise at a global signal-to-noise ratio (SNR) corrupts the speech signal non-uniformly over different smaller duration temporal regions, the goal is to find which temporal regions are relatively clean and thereby more useful for speaker recognition. These useful temporal regions are known as the regions of 'usable speech' [4]. The student is currently testing a novel algorithm to blindly detect 'usable speech' and is expected to graduate in one year's time.…”

Section: Example Of An Electrical and Computer Engineering Studentmentioning

confidence: 99%

Conducting State-of the-art Research in an Institution with a Strong Undergraduate Education Focus

Mehta¹,

Dusseau²,

Ramachandran³

2013 ASEE Annual Conference &Amp; Exposition Proceedings

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Usable Speech Processing: A Filterless Approach in the Presence of Interference

Cited by 17 publications

References 16 publications

Vertical Integration of Biometrics Across the Curriculum: Case Study of Speaker, Face and Iris Recognition

Vertical Integration of Biometrics Across the Curriculum: Case Study of Speaker, Face and Iris Recognition

Overlapped-speech detection with applications to driver assessment for in-vehicle active safety systems

Conducting State-of the-art Research in an Institution with a Strong Undergraduate Education Focus

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