The perception of code-switched vs. monolingual sentences in TTS voices

This study examines the intelligibility of English and Spanish lexical items in code-switched utterances across different text-to-speech (TTS) synthesis methods. Using stimuli generated with neural and concatenative TTS, 49 Spanish-English bilingual participants listened to 96 sentences, mixed with noise, and typed the phrase-final keyword. Half of the sentences contained English-Spanish code-switches (equal number of English and Spanish target keywords), and half were monolingual sentences (half English, half Spanish). Accuracy was coded binomially for correct word identification. Results show that intelligibility is lower: (1) when the target words are produced in Spanish, and (2) in code-switched conditions. These results are in contrast with previous work showing intelligibility differences between TTS conditions. Moreover, the lower intelligibility results in the Spanish target word sentences and code-switched conditions present motivations for improving voice-AI speech to include common bilingual practices.

Authors

Institutions

Publication Details

Journal
Frontiers in Computer Science
Published
2025-08-12
DOI
https://doi.org/10.3389/fcomp.2025.1565604
Primary Topic
Language, Discourse, Communication Strategies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The perception of code-switched vs. monolingual sentences in TTS voices

Georgia Zellou, Tyler Méndez Kline
Frontiers in Computer Science
Language, Discourse, Communication Strategies
article

The perception of code-switched vs. monolingual sentences in TTS voices

Georgia Zellou, Tyler Méndez Kline
article en

Abstract

This study examines the intelligibility of English and Spanish lexical items in code-switched utterances across different text-to-speech (TTS) synthesis methods. Using stimuli generated with neural and concatenative TTS, 49 Spanish-English bilingual participants listened to 96 sentences, mixed with noise, and typed the phrase-final keyword. Half of the sentences contained English-Spanish code-switches (equal number of English and Spanish target keywords), and half were monolingual sentences (half English, half Spanish). Accuracy was coded binomially for correct word identification. Results show that intelligibility is lower: (1) when the target words are produced in Spanish, and (2) in code-switched conditions. These results are in contrast with previous work showing intelligibility differences between TTS conditions. Moreover, the lower intelligibility results in the Spanish target word sentences and code-switched conditions present motivations for improving voice-AI speech to include common bilingual practices.

Frontiers in Computer ScienceVol. 7
University of California, Davis (US), University of California, Berkeley (US)
Openalex Percentile: Top 74%
Language, Discourse, Communication Strategies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.