In this paper we present a hybrid statistical and rule-based segmentation system which takes into account phonetic variation of German. Input to the system is the orthographic representation and the speech signal of an utterance to be segmented. The output is the transcription (SAM-PA) with the highest overall likelihood and the corresponding segmentation of the speech signal. The system consis...

In this paper we discuss a speaker identification approach, called ASR-dependent speaker identification, that incorporates phonetic knowledge into the models for each speaker. This approach differs from traditional methods for performing textindependent speaker identification, such as global Gaussian mixture modeling, that typically ignore the phonetic content of the speech signal. We introduce...

We describe an approach to grapheme-to-phoneme conversion which is both language-independent and data-oriented. Given a set of examples (spelling words with their associated phonetic representation) in a language, a grapheme-to-phoneme conversion system is automatically produced for that language which takes as its input the spelling of words, and produces as its output the phonetic transcripti...

Two experiments were carried out to evaluate the perceptual effect of various enhancements made to information-rich regions of intervocalic consonants. The first tested the benefits of altering the relative amplitude of such regions, whilst the second additionally employed filtering to produce stylised cues to phonetic contrasts. After such manipulations stimuli were combined with speech-shaped...

In this paper, the acoustic–phonetic characteristics of American English stop consonants are investigated. Features studied in the literature are evaluated for their information content and new features are proposed. A statistically guided, knowledge-based, acoustic–phonetic system for the automatic classification of stops, in speaker independent continuous speech, is proposed. The system uses ...

In this work we investigate new inter-phone and inter-word distances and we apply them to predict if two words of the lexicon of an Automatic Speech Recognition (ASR) system are likely to be confused. The inter-word distance is calculated from an alignment between the phonetic transcriptions of the words by adding the distances between the aligned phones. We bring a new solution in which the in...

We present methods of detector design in the Automatic Speech Attribute Transcription project. This paper details the results of a student-led, cross-site collaboration between Georgia Institute of Technology, The Ohio State University and Rutgers University. The work reported in this paper describes and evaluates the detection-based ASR paradigm and discusses phonetic attribute classes, method...

This study attempts to improve automatic phonetic segmentation within the HMM framework. Experiments were conducted to investigate the use of phone boundary models, the use of precise phonetic segmentation for training HMMs, and the difference between context-dependent and contextindependent phone models in terms of forced alignment performance. Results show that the combination of special one-...

Phonology provides a system by which a limited number of types of phonetic variation can signal communicative intentions at multiple levels of linguistic analysis. Because phonologies vary from language to language, acquiring the phonology of a language demands learning to attribute phonetic variation appropriately. Here, we studied the case of pitch-contour variation. In English, pitch contour...

During early language acquisition, infants must learn both a lexicon and a model of phonetics that explains how lexical items can vary in pronunciation—for instance “the” might be realized as [Di] or [D@]. Previous models of acquisition have generally tackled these problems in isolation, yet behavioral evidence suggests infants acquire lexical and phonetic knowledge simultaneously. We present a...