Results 331 to 340 of about 679,191 (389)
Detecting Forged Audio Files Using "Mixed Paste" Command: A Deep Learning Approach Based on Korean Phonemic Features. [PDF]
Sensors (Basel)Son Y, Park JW.
europepmc +1 more source
Developing automaticity in neural speech discrimination in typically developing bilingual Italian-German and monolingual German children. [PDF]
PLoS OneBloder T, Rinker T, Shafer V.
europepmc +1 more source
Some of the next articles are maybe not open access.
Related searches:
Related searches:
Is a stop consonant released when followed by another stop consonant?
The Journal of the Acoustical Society of America, 1981Phoneticians have generally claimed that, in sequences of two-stop consonants in English, the first stop is often unreleased. To examine this claim, we recorded sentences, produced by several native speakers of American English at a conversational rate, containing disyllabic words with one of the 24 possible sequences of two nonhomorganic stops across ...
Janette B. Henderson, Bruno H. Repp
openaire +4 more sources
Contrast effects on stop consonant identification.
Journal of Experimental Psychology: Human Perception and Performance, 1978Changes in the identification of speech sounds following selective adaptation are usually attributed to a reduction in sensitivity of auditory feature detectors. An alternative explanation of these effects is based on the notion of response contrast. In several experiments, subjects identified the initial segment of synthetic consonant-vowel syllables ...
Randy L. Diehl +2 more
openaire +4 more sources
Spectral tilt change in stop consonant perception
The Journal of the Acoustical Society of America, 2008There exists no clear understanding of the importance of spectral tilt for perception of stop consonants. It is hypothesized that spectral tilt may be particularly salient when formant patterns are ambiguous or degraded. Here, it is demonstrated that relative change in spectral tilt over time, not absolute tilt, significantly influences perception of ...
Keith R. Kluender, Joshua M. Alexander
openaire +4 more sources
Linguistics Vanguard, 2018
The present study investigates patterns of covariation among acoustic properties of stop consonants in a large multi-talker corpus of American English connected speech.
Eleanor Chodroff, Colin Wilson
semanticscholar +1 more source
The present study investigates patterns of covariation among acoustic properties of stop consonants in a large multi-talker corpus of American English connected speech.
Eleanor Chodroff, Colin Wilson
semanticscholar +1 more source
2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)., 2003
To extract speech from acoustic interference is a challenging problem. Previous systems based on auditory scene analysis principles deal with voiced speech, but cannot separate unvoiced speech. We propose a novel method to separate stop consonants, which contain significant unvoiced signals, based on their acoustic properties.
Guoning Hu, DeLiang Wang
openaire +2 more sources
To extract speech from acoustic interference is a challenging problem. Previous systems based on auditory scene analysis principles deal with voiced speech, but cannot separate unvoiced speech. We propose a novel method to separate stop consonants, which contain significant unvoiced signals, based on their acoustic properties.
Guoning Hu, DeLiang Wang
openaire +2 more sources
The structure of Hindi stop consonants
The Journal of the Acoustical Society of America, 2016The pronunciation of stop consonants varies markedly with age, gender, accent, etc. Yet by extracting appropriate cues common to these varying pronunciations, it is possible to correctly identify the spoken consonant. In this paper, the structure underlying Hindi stop consonants is presented. This understanding may potentially be used as a “recipe” for
Nachiketa Tiwari, Kushagra Singh
openaire +3 more sources
The Silent Interval of Stop Consonants
Language and Speech, 1974An experiment was conducted to measure the silent interval (SI) preceding the burst of all the stop consonants in English. A list of words was constructed for each pair of stop cognates. More commonly used words with stop cognates in similar environments were chosen for the experiment.
Michael P. Beddoes, Ching Y. Suen
openaire +2 more sources
Computer recognition of stop consonants
ICASSP '79. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005The paper describes a computer program for the automatic recognition of stop consonants in continuous speech. The recognition is performed by a fuzzy algorithm that accounts for the imprecision of the features extracted and of the rules. The rules belong to a fuzzy grammar and account for coarticulation and contextual effects.
P. Demichelis +3 more
openaire +2 more sources