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Updated: May 30, 2026

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
Published on: September 27, 2024
Processing of no-release variants in connected speech
Paul C LoCasto1, Cynthia M Connine
1Department of Psychology, Quinnipiac University, 275 Mt. Carmel Ave., CLAC I, Hamden, CT 06518, USA. paul.locasto@quinnipiac.edu
This study explored how ambiguous speech sounds are processed during word recognition. Findings suggest that the frequency of sound occurrences and surrounding sounds influence spoken word recognition and lexical competition.
Area of Science:
- Psycholinguistics
- Speech Perception
- Cognitive Science
Background:
- Spoken word recognition involves complex processes influenced by phonetic and lexical factors.
- Lexical ambiguity, where a sound can belong to multiple words, presents a challenge for speech processing.
- No-release variants, where a consonant sound is not fully articulated, add another layer of complexity.
Purpose of the Study:
- To investigate the processing of lexically ambiguous no-release speech variants.
- To examine the role of segmental regularities (voicing, phonological context) in the frequency of these variants.
- To understand how these factors influence spoken word recognition and lexical competition.
Main Methods:
- Utilized the cross-modal repetition priming paradigm.
- Manipulated primes based on carrier words ending in voiced (e.g., BAND) or voiceless (e.g., PLANT) segments, followed by consonant or vowel onset context words.
- Employed both carrier words and true embedded words (e.g., 'plan' from 'plant') as visual targets.
Main Results:
- Probabilistic speech events, influenced by segment voicing and phonological context, significantly affect spoken word recognition.
- The frequency of occurrence of no-release variants plays a crucial role in resolving lexical ambiguity.
- Evidence supports the interaction between phonetic properties and lexical access in real-time word recognition.
Conclusions:
- Probabilistic information derived from speech input is integral to spoken word recognition models.
- The study highlights the dynamic interplay between phonetic detail and lexical knowledge.
- Findings contribute to a deeper understanding of how listeners resolve ambiguity in continuous speech.
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