Language and gender effects in the phonetics of parentese

Parentese is the typical register for talking to children. Its segment-marking prosody can disambiguate messages. This study documents acoustic-phonetic features of parentese in English and Dutch and compares male and female speakers. Speech rate was significantly lower; pitch and pitch modulation were significantly higher. Male and female 'parentese substyles' emerged

Punctuation Restoration for Singaporean Spoken Languages: English, Malay, and Mandarin

This paper presents the work of restoring punctuation for ASR transcripts generated by multilingual ASR systems. The focus languages are English, Mandarin, and Malay which are three of the most popular languages in Singapore. To the best of our knowledge, this is the first system that can tackle punctuation restoration for these three languages simultaneously. Traditional approaches usually treat the task as a sequential labeling task, however, this work adopts a slot-filling approach that predicts the presence and type of punctuation marks at each word boundary. The approach is similar to the Masked-Language Model approach employed during the pre-training stages of BERT, but instead of predicting the masked word, our model predicts masked punctuation. Additionally, we find that using Jieba1 instead of only using the built-in SentencePiece tokenizer of XLM-R can significantly improve the performance of punctuating Mandarin transcripts. Experimental results on English and Mandarin IWSLT2022 datasets and Malay News show that the proposed approach achieved state-of-the-art results for Mandarin with 73.8% F1-score while maintaining a reasonable F1-score for English and Malay, i.e. 74.7% and 78% respectively. Our source code that allows reproducing the results and building a simple web-based application for demonstration purposes is available on Github

Directions for the future of technology in pronunciation research and teaching

This paper reports on the role of technology in state-of-the-art pronunciation research and instruction, and makes concrete suggestions for future developments. The point of departure for this contribution is that the goal of second language (L2) pronunciation research and teaching should be enhanced comprehensibility and intelligibility as opposed to native-likeness. Three main areas are covered here. We begin with a presentation of advanced uses of pronunciation technology in research with a special focus on the expertise required to carry out even small-scale investigations. Next, we discuss the nature of data in pronunciation research, pointing to ways in which future work can build on advances in corpus research and crowdsourcing. Finally, we consider how these insights pave the way for researchers and developers working to create research-informed, computer-assisted pronunciation teaching resources. We conclude with predictions for future developments

Suprasegmental speech perception, working memory and reading comprehension in Cantonese-English bilingual children

This study set out to examine (a) lexical tone and stress perception by bilingual and monolingual children, (b) interrelationships between lexical pitches perception, general acoustic mechanism and working memory, and (c) the association between lexical tone awareness and Chinese text reading comprehension. Experiment 1 tested and compared the perception of Cantonese lexical tones, English lexical stress and nonlinguistic pitch between Cantonese-English bilingual and English monolingual children. The relationships between linguistic pitch perception, non-linguistic pitch perception and working memory were also examined among Cantonese-English bilingual children. Experiment 2 explored the relationship between Cantonese tone awareness and Chinese text reading comprehension skills. Results of this study illustrate differential performances in tone perception but similar performances in stress perception between bilinguals and monolinguals. In addition, inter-correlations were found between linguistic pitches perception, general acoustic mechanism, working memory and reading comprehension. These findings provide new insight to native and non-native perception of lexical pitches, and demonstrate an important link that exists between lexical tone awareness and reading comprehension.published_or_final_versionSpeech and Hearing SciencesBachelorBachelor of Science in Speech and Hearing Science

A computational model for studying L1’s effect on L2 speech learning

abstract: Much evidence has shown that first language (L1) plays an important role in the formation of L2 phonological system during second language (L2) learning process. This combines with the fact that different L1s have distinct phonological patterns to indicate the diverse L2 speech learning outcomes for speakers from different L1 backgrounds. This dissertation hypothesizes that phonological distances between accented speech and speakers' L1 speech are also correlated with perceived accentedness, and the correlations are negative for some phonological properties. Moreover, contrastive phonological distinctions between L1s and L2 will manifest themselves in the accented speech produced by speaker from these L1s. To test the hypotheses, this study comes up with a computational model to analyze the accented speech properties in both segmental (short-term speech measurements on short-segment or phoneme level) and suprasegmental (long-term speech measurements on word, long-segment, or sentence level) feature space. The benefit of using a computational model is that it enables quantitative analysis of L1's effect on accent in terms of different phonological properties. The core parts of this computational model are feature extraction schemes to extract pronunciation and prosody representation of accented speech based on existing techniques in speech processing field. Correlation analysis on both segmental and suprasegmental feature space is conducted to look into the relationship between acoustic measurements related to L1s and perceived accentedness across several L1s. Multiple regression analysis is employed to investigate how the L1's effect impacts the perception of foreign accent, and how accented speech produced by speakers from different L1s behaves distinctly on segmental and suprasegmental feature spaces. Results unveil the potential application of the methodology in this study to provide quantitative analysis of accented speech, and extend current studies in L2 speech learning theory to large scale. Practically, this study further shows that the computational model proposed in this study can benefit automatic accentedness evaluation system by adding features related to speakers' L1s.Dissertation/ThesisDoctoral Dissertation Speech and Hearing Science 201