Understanding the Lombard Effect for Mandarin: Relation Between Speech Recognition Thresholds and Acoustic Parameters

Abstract

The present work quantifies the Lombard effect across native speakers of Mandarin Chinese using the Matrix sentence test, which is optimized for precisely assessing speech recognition thresholds (SRTs) in noise. Specifically, we studied the effects of speaker gender, fundamental frequency (F0), formant frequencies (F1 and F2), the duration and rate of voiced segments, and frequency-specific energy redistribution characterized by alpha ratio and speech-weighted signal-to-noise ratio (swSNR) on the recognition of Mandarin in plain and Lombard speech. The Mandarin Chinese matrix test was recorded with plain and Lombard speech from 11 native-Mandarin speakers. SRTs in stationary noise were measured with native-Mandarin, normal-hearing listeners. Results showed that on average, Mandarin Lombard speech was more intelligible than Mandarin plain speech for both female and male speakers, and the Mandarin Lombard gain of female speakers was larger than that of males. In addition, various acoustic analyses involving all speakers showed that (a) only swSNR was significantly correlated with the SRT of the Mandarin plain speech; (b) most acoustic measures were significantly correlated with the SRT of the Mandarin Lombard speech; and (c) alpha ratio and swSNR were significantly correlated with the SRT Lombard gain. In addition, a gender effect was found in the correlational analysis between acoustic parameters and SRT as well as Lombard gain in SRT. The findings highlight the impact of increased high-frequency energy on the observed Lombard gain in Mandarin speech, whereas the changes in individual acoustic parameters (e.g., F0 and F1) appear to play only a minor role.

Keywords: Lombard effect; SRT Lombard gain; alpha ratio; speech recognition threshold; speech-weighted signal-to-noise ratio (swSNR).

Figure 1.

(a) Speech recognition thresholds (SRTs) averaged across speakers and listeners under all listening conditions. Asterisks denote a significant (P < 0.05) difference between the SRTs of the paired conditions. (b) Empirical Lombard gains for female and male speakers across all listeners. The error bars denote ±1 standard error of the mean.

Figure 2.

SRTs with corresponding standard errors of the Mandarin plain and Lombard speech of all speakers. Asterisks denote that the SRTs difference between plain and Lombard speech are significant (P < 0.0045) or non-significant (P > 0.0045), respectively. ‘SF’ and ‘SM’ denote female and male speakers, respectively.

Figure 3.

Mean values of acoustic parameters for Mandarin plain and Lombard speech of different speaker groups. Panels (a), (b), (c), (d), (e), (f) and (g) are for alpha ratio, swSNR, F0, F1, F2, duration of voiced segments, and rate of voiced segments, respectively. Asterisks denote a significant (P < 0.05) difference between the SRTs of the paired conditions. The error bars denote ±1 standard error of the mean. ‘all’, ‘male’ and ‘female’ denote the comparisons involving all speakers, male speakers, and female speakers, respectively.

Figure 4.

Scatter plots between SRT and swSNR for the plain speech of (a) all speakers, (b) male speakers, and (c) female speakers, and for the Lombard speech of (d) all speakers, (e) male speakers, and (f) female speakers. The lowest row depicts scatter plots between empirical Lombard gain in SRT and Lombard gain in swSNR for (g) all speakers, (h) male speakers, and (i) female speakers.