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Unsupervised phone segmentation means that the phone boundaries in an utterance can be detected without a prior knowledge about the text contents. Usually, a spectral change in the speech signal implies the existence of a phone boundary. In this paper, the Delta Spectral Function (DSF) is defined for each frame to represent the variation of band energy for a specific band. Then a number of bands that...
The reliable detection of salient acoustic-phonetic cues in speech signal plays an important role in speech recognition based on speech landmarks. Once speech landmarks are located, not only can phone recognition be performed, but other useful information can also be derived. This paper focuses on the detection of burst onset landmarks, which are crucial to the recognition of stop and affricate consonants...
To annotate voice onset time (VOT) of stop consonants in a speech database, manually labeling is a feasible but time-consuming and tedious task. This paper proposed a fully-automatic VOT estimation method to alleviate this burden. The method relies on an HMM-based phone recognizer and a random forest (RF) based onset detector. The phone recognizer performs a forced alignment to locate stop consonants,...
Reliably detecting salient phonetic-acoustic cues plays an important role in speech recognition based on speech landmarks. Once these speech landmarks are located, not only phone recognition can be performed but some other useful information can be derived as well. This paper focuses on the topic of detecting burst onset landmark, an important phonetic characteristic in stops and affricates. The proposed...
The non-stationary behavior makes stops classification one of worthy examining subject in the speech community. Over several decades, many researchers have sorted out a list of acoustic properties that are useful to identify a stop. In this paper, we extract features that are sufficient to represent the important acoustic properties of stops, like statistic moments of the burst spectrum. In combining...
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