Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Summary

This research aimed to make a comparison between L1-L2-English and L1-L2 Portuguese to check how much the effect of a foreign accent accounts for both metrics and prosodic-acoustic parameters, as well as for the choice of the target voice in a voice lineup.

Abstract

This research aims to examine both the prosodic-acoustic features and the perceptual correlates of foreign-accented English and foreign-accented Brazilian Portuguese and check how the speakers' productions of foreign and native accents are correlated to the listeners' perception. In the Methodology, we conducted a speech production procedure with a group of American speakers of L2 Brazilian Portuguese and a group of Brazilian speakers of L2 English, and a speech perception procedure in which we performed voice lineups for both languages.For the speech production statistical analysis, we ran Generalized Additive Models to evaluate the effect of the language groups on each class (metric or prosodic-acoustic) of features controlled for the smoothing effect of the covariate(s) of the opposite class. For the speech perception statistical analysis, we ran a Kruskal-Wallis test and a post-hoc Dunn's test to evaluate the effect of the voices of the lineups on the scores judged by the listeners. We nevertheless conducted acoustic (voice) similarity tests based on Cosine and Euclidean distances. Results showed significant acoustic differences between the language groups in terms of variability of the f0, duration, and voice quality. For the lineups, the results indicated that prosodic features of f0, intensity, and voice quality correlated to the listeners' perceived judgments.

Introduction

The accent is a salient and dynamic aspect of communication and fluency, both in the native language (L1) and in a foreign language (L2)¹. Foreign accent represents the L2 phonetic features of a target language, and it can change (over time)in response to the speaker’s L2 experience, speaking style, input quality, exposition, among other variables. A foreign accent can be quantified as a (scalar) degree of difference between L2 speech produced by a foreign speaker and a local or reference accent of the target language^2,3,....

Protocol

This work received approval from a human research ethics committee. Furthermore, informed consent was obtained from all participants involved in this study to use and publish their data.

1. Speech production

NOTE: We collected speech from a reading task on both 'L1 English-L2 BP' produced by Group 1: The American English (from the U.S.A.) Speakers (AmE-S), and on both 'L1 .......

Discussion

The current protocol presents a novelty in the field of (forensic) phonetics. It is divided into two phases: one based on production (acoustic analysis) and one based on perception (judgement analysis). The production analysis phase comprises the Data preparation and Forced alignment, Realignment, and Automatic extraction of prosodic-acoustic features besides the statistics. This protocol connects the stage of data collection to the data analysis in a faster and more efficient way than the traditional protocols based on .......

Materials

Name	Company	Catalog Number	Comments
CreateLineup	Personal collection	#	Script for praat for voice lineups preparation
Dell I3 (with solid-state drive - SSD)	Dell	#	Laptop computer
Praat	Paul Boersma & David Weenink	#	Software for phonetic analysis
Python 3	Python Software Foundation	#	Interpreted, high-level, general-purpose programming language
R	The R Project for Statistical Computing	#	Programming language for stattistical computing
Shure Beta SM7B	Shure	#	Microphone
SpeechRhythmExtractor	Personal collection	#	Script for praat for automatic extraction of acoustic features
SurveyMonkey	SurveyMonkey Inc.	#	Assemble of free customizable surveys, as well as a suite of back-end programs that include data analysis, sample selection, debiasing, and data representation.
Tascam DR-100 MKII	Tascam	#	Digital voice recorder
The Munich Automatic Segmentation System MAUS	University of Munich	#	Forced-aligner of audio (.wav) and linguistic information (.txt) files
VVUnitAligner	Personal collection	#	Script for praat for automatic realignment and post-processing of phonetic units