In this paper, we present a robust acoustic feature on top of robust modeling techniques to further improve speaker identification performance.
All for one: Feature combination for highly channel-degraded speech activity detection
This paper presents a feature combination approach to improve SAD on highly channel degraded speech as part of the Defense Advanced Research Projects Agency’s (DARPA) Robust Automatic Transcription of Speech (RATS) program.
A Noise-Robust System for NIST 2012 Speaker Recognition Evaluation
This paper presents SRI’s submission along with a careful analysis of the approaches that provided gains for this challenging evaluation including a multiclass voice-activity detection system, the use of noisy data in system training, and the fusion of subsystems using acoustic characterization metadata.
Improving Speaker Identification Robustness to Highly Channel-Degraded Speech Through Multiple System Fusion
This article describes our submission to the speaker identification (SID) evaluation for the first phase of the DARPA Robust Audio and Transcription of Speech (RATS) program.
Effects of audio and ASR quality on cepstral and high-level speaker verification systems
We evaluate the effect that improved audio quality has for speaker verification performance, using a recently released full-bandwidth version of microphone data from the SRE2010 evaluation.
Normalized amplitude modulation features for large vocabulary noise-robust speech recognition
In this work, we present an amplitude modulation feature derived from Teager’s nonlinear energy operator that is power normalized and cosine transformed to produce normalized modulation cepstral coefficient (NMCC) features…
Towards Noise-Robust Speaker Recognition Using Probabilistic Linear Discriminant Analysis
This work addresses the problem of speaker verification where additive noise is present in the enrollment and testing utterances.
Promoting robustness for speaker modeling in the community: the PRISM evaluation set
We introduce a new database for evaluation of speaker recognition systems.
Bird species recognition combining acoustic and sequence modeling
The goal of this work was to explore modeling techniques to improve bird species classification from audio samples.