Noise Be Gone: Does Speech Enhancement Distort Linguistic Nuances? (2024)

Abstract: This study evaluates the impact of speech enhancement (SE) techniques on linguistic research, focusing on their ability to maintain essential acoustic characteristics in enhanced audio without introducing significant artifacts. Through a sociophonetic analysis of Peninsular and Peruvian Spanish speakers, using both original and enhanced recordings, we demonstrate that SE effectively preserves critical speech nuances such as voicing and vowel quality. This supports the use of SE in improving the quality of speech samples. This study marks an initial effort to assess SE’s reliability in language studies and proposes a methodology for enhancing low-quality audio corpora of under-resourced languages.

## introduction speech is a fundamental mode of human communication, consisting primarily of two components: speech production and speech perception @xcite . speech production enables individuals to articulate ideas through sound using linguistic structures. conversely, speech perception involves the decoding of sound waves generated during speech production. these processes can be influenced by external factors such as ambient or background noise, potentially disrupting the communication sequence @xcite . humans have evolved mechanisms to filter out these disturbances @xcite @xcite . however, audio recordings capture both desired and undesired signals indiscriminately. this poses significant challenges for sociophonetic research, which often relies on pre-recorded audio data. speech enhancement (se) techniques clean and filter these recordings from external noise, thus enhancing the perceptual quality of the speech @xcite and y (j) n represent vocalic /e/ (e.g., /bre/) and /i/ (e.g., /li/) tokens respectively. the original tokens are copied. one version is stored in the final dataset, while the other is processed as explained above to provide the enhanced copies y (i) n ′ and y (j) n ′ . the final dataset includes all tokens, original and enhanced. the reliability of speech enhancement models in improving the quality of linguistic speech corpora remains an open question. sociophonetic studies, which explore speech variations among different social groups, provide a robust framework for testing se models to ensure they maintain essential acoustic characteristics (e.g., vowel quality or voicing). moreover, these methodologies often focus on subtle speech variations, making them ideal for assessing the ability of se models to retain these nuances post-enhancement. this study seeks to evaluate the effects of se on linguistic corpora by conducting paired sociophonetic studies. we present a case study that examines the voicing and duration of intervocalic voiceless fricatives, as well as vocalic quality variations between peninsular and peruvian spanish speakers. our findings indicate that the studies using original and enhanced recordings yield comparable results. to our knowledge, this is the first work (1) address-ing such questions from a linguistic viewpoint and (2) proposing a novel methodological approach for handling low-quality audio data in linguistic studies. ## previous work although there is ongoing research into the bias introduced by enhanced recordings @xcite , the linguistic community continues to debate the risk of distorting results through potential artifact introduction during enhancement. previous technologies like wavenet @xcite have shown the ability to replicate speech with particular linguistic and acoustic subtleties @xcite ; however, further exploration in this area is limited. most of the sociophonetics studies dealing with technology have focused on audio quality. @xcite studied the usability of zoom as a tool for recording speech data. they found that f1 and f2 values showed significant differences compared to speech recorded with specialized equipment. @xcite look at how different normalization methods affect recordings with different degrees of quality, showing that normalization procedures may be relevant to address technical factors in low-quality recordings. background noise has also been a central topic for perceptual studies, which coincide in that it should be eliminated as much as possible @xcite . to this issue, filtering @xcite , especially low-pass, may be useful; however, there is a risk of deleting relevant nuances of speech production. overall, while some works have used methodologies borrowed from linguistics @xcite , se has not had much attention in the field. avoiding hard filtering is crucial to analyzing high-frequencies (hf) content-heavy speech. studies have gradually recognized the importance of retaining hf content in speech signals @xcite , particularly when analyzing fricatives @xcite . fricatives, which are rich in highfrequency energy, have shown to play a significant role in distinguishing phonetic and phonological features @xcite . in the context of peruvian spanish and peninsular spanish, analyzing the voicing of fricatives before and after enhancement is particularly insightful. @xcite offered a detailed description of pe-ruvian and peninsular spanish and morrison et al. (2007) compared vocalic sounds in both variations, showing that peruvian speakers reproduced higher fundamental frequency values. ## conclusion in this study, we have analyzed the impact of speech enhancement (se) on the audio properties of fricative and vocalic sounds in spanish. we use a sociophonetic case study to test whether results are consistent across original and audio-enhanced tokens. we analyzed the results for voicing and du-ration in intervocalic /s/, comparing paired models fitted on original and enhanced data. we also inspected the impact of condition as an independent variable on voicing and duration. in the sociophonetic dimension, our analyses show that while demographic factors such as gender and geographic origin influence certain phonetic features like frication duration, they have minimal impact on others such as voicing. regarding condition, the experimental manipulation of audio enhancement did not significantly alter the outcomes, indicating robustness in preserving phonetic characteristics. we found no evidence suggesting that the enhanced tokens significantly modified or contaminated the statistical results. experiments in vocalic quality showed a similar trend. the features captured by the pca coincide with previous literature on the comparison between peruvian and peninsular vowels. we show that se tokens preserve essential acoustic characteristics of vocalic sounds across different spanish-speaking populations. the high correlations and significant outputs across all demographic groups reinforce the reliability of the results. these findings hold the potential to yield advantageous results for languages with limited resources, which usually have lower-quality speech corpora. by demonstrating the robust preservation of acoustic properties and sociophonetic markers, this study supports the effectiveness of speech enhancement for data in which linguistic nuances are critical.