The Influence of Sensorineural Hearing Loss on the Relationship Between the Perception of Speech in Noise and Dysarthric Speech.

PURPOSE: The ability to understand speech under adverse listening conditions is highly variable across listeners. Despite this, studies have found that listeners with normal hearing display consistency in their ability to perceive speech across different types of degraded speech, suggesting that, for at least these listeners, global skills may be involved in navigating the ambiguity in speech signals. However, there are substantial differences in the perceptual challenges faced by listeners with normal and impaired hearing. This study examines whether listeners with sensorineural hearing loss demonstrate the same type of consistency as normal-hearing listeners when processing neurotypical (i.e., control) speech that has been degraded by external noise and speech that is neurologically degraded such as dysarthria. METHOD: Listeners with normal hearing (n = 31) and listeners with sensorineural hearing loss (n = 36) completed an intelligibility task with neurotypical speech in noise and with dysarthric speech in quiet. RESULTS: Findings were consistent with previous work demonstrating a relationship between the ability to perceive neurotypical speech in noise and dysarthric speech for listeners with normal hearing, albeit at a higher intelligibility level than previously observed. This relationship was also observed for listeners with hearing loss, although listeners with more severe hearing losses performed better with dysarthric speech than with neurotypical speech in noise. CONCLUSIONS: This study demonstrated a high level of consistency in intelligibility performance for listeners across two different types of degraded speech, even when those listeners were further challenged by the presence of sensorineural hearing loss. Clinical implications for both listeners with hearing loss and their communication partners with dysarthria are discussed.

The Application of Time-Frequency Masking To Improve Intelligibility of Dysarthric Speech in Background Noise.

PURPOSE: Background noise reduces speech intelligibility. Time-frequency (T-F) masking is an established signal processing technique that improves intelligibility of neurotypical speech in background noise. Here, we investigated a novel application of T-F masking, assessing its potential to improve intelligibility of neurologically degraded speech in background noise. METHOD: Listener participants (N = 422) completed an intelligibility task either in the laboratory or online, listening to and transcribing audio recordings of neurotypical (control) and neurologically degraded (dysarthria) speech under three different processing types: speech in quiet (quiet), speech mixed with cafeteria noise (noise), and speech mixed with cafeteria noise and then subsequently processed by an ideal quantized mask (IQM) to remove the noise. RESULTS: We observed significant reductions in intelligibility of dysarthric speech, even at highly favorable signal-to-noise ratios (+11 to +23 dB) that did not impact neurotypical speech. We also observed significant intelligibility improvements from speech in noise to IQM-processed speech for both control and dysarthric speech across a wide range of noise levels. Furthermore, the overall benefit of IQM processing for dysarthric speech was comparable with that of the control speech in background noise, as was the intelligibility data collected in the laboratory versus online. CONCLUSIONS: This study demonstrates proof of concept, validating the application of T-F masks to a neurologically degraded speech signal. Given that intelligibility challenges greatly impact communication, and thus the lives of people with dysarthria and their communication partners, the development of clinical tools to enhance intelligibility in this clinical population is critical.

Family Involvement in Adult Hearing Evaluation Appointments: Patient Perspectives.

Background Many adults suffer from an array of consequences due to their hearing loss (e.g., self-efficacy, mastery, psychosocial challenges). Family involvement can help improve their outcomes. Purpose This study aimed to determine audiology adult patients hearing experiences and inquired about their perspectives on family involvement in appointments. Research Design A cross-sectional survey was completed. Descriptive statistics, item analyses, and quantitative analyses were used to examine patient's characteristics and perspectives. Study Sample Three hundred eighty-two adult audiology patients participated in the study. Data Collection and Analysis A 15-item survey was created with 4 sections, including patient demographic information, general hearing questions, hearing experiences, and family interactions and involvement. Descriptive statistics were used to examine patient's characteristics and perspectives on family involvement in audiology appointments. Chronbach's alpha was used to reveal good internal consistency of difficult feelings related to hearing and perceived negative family member reactions. Quantitative analyses were used to determine patient perspectives on family involvement. Results Though patients reported difficulties due to their hearing loss, more than half reported that they did not want family involvement or they were unsure of the benefit that the involvement would provide. Patients who were interested in having family involved reported benefits such as educational opportunities and support. Few barriers of family involvement were reported by patients. Conclusions Patients had a mixed desire about family involvement in their adult audiology appointments. Education of patients about the benefits of family involvement may need to happen for this shift in audiologic practice.

Confidence of School-Based Speech-Language Pathologists and School Psychologists in Assessing Students With Hearing Loss and Other Co-Occurring Disabilities.

Purpose This study assessed the confidence of speech-language pathologists (SLPs) and school psychologists (SPs) in working with children with hearing loss (HL) and other co-occurring disabilities. Professionals' opinions on barriers to and importance of interdisciplinary collaboration were also of interest. Method A 59-item online survey was distributed to SLPs and SPs in the United States through state professional organizations and social media posts. A total of 320 respondents completed the survey and met criteria. Perceptions of confidence across 5 different skill set types were assessed, along with experiences and attitudes concerning professional training and interdisciplinary collaboration. Results A 2-way analysis of variance revealed significant main effects of profession and skill set type on professionals' confidence in assessing a student with HL and other co-occurring disabilities, as well as their confidence in determining the etiology of a student's difficulties. Results from a multiple linear regression revealed the number of students worked with who have HL and the amount of training in graduate school as significant predictors of confidence in both aforementioned skill set types. Results indicate that respondents value interdisciplinary collaboration but that time and access to other professionals are barriers to collaboration. Conclusions Results of the current study indicate that many school-based SLPs and SPs have insufficient training or experience in working with students who have HL and other co-occurring disabilities. Limited training and experience with this unique population among practitioners have the potential to affect the quality of services provided to these students and thus need to be addressed within the school system and the fields of school psychology and speech-language pathology. Supplemental Material https://doi.org/10.23641/asha.7772867.

Individualized frequency importance functions for listeners with sensorineural hearing loss.

The Speech Intelligibility Index includes a series of frequency importance functions for calculating the estimated intelligibility of speech under various conditions. Until recently, techniques to derive frequency importance required averaging data over a group of listeners, thus hindering the ability to observe individual differences due to factors such as hearing loss. In the current study, the "random combination strategy" [Bosen and Chatterjee (2016). J. Acoust. Soc. Am. 140, 3718-3727] was used to derive frequency importance functions for individual hearing-impaired listeners, and normal-hearing participants for comparison. Functions were measured by filtering sentences to contain only random subsets of frequency bands on each trial, and regressing speech recognition against the presence or absence of bands across trials. Results show that the contribution of each band to speech recognition was inversely proportional to audiometric threshold in that frequency region, likely due to reduced audibility, even though stimuli were shaped to compensate for each individual's hearing loss. The results presented in this paper demonstrate that this method is sensitive to factors that alter the shape of frequency importance functions within individuals with hearing loss, which could be used to characterize the impact of audibility or other factors related to suprathreshold deficits or hearing aid processing strategies.

Autoscore: An open-source automated tool for scoring listener perception of speech.

Speech perception studies typically rely on trained research assistants to score orthographic listener transcripts for words correctly identified. While the accuracy of the human scoring protocol has been validated with strong intra- and inter-rater reliability, the process of hand-scoring the transcripts is time-consuming and resource intensive. Here, an open-source computer-based tool for automated scoring of listener transcripts is built (Autoscore) and validated on three different human-scored data sets. Results show that not only is Autoscore highly accurate, achieving approximately 99% accuracy, but extremely efficient. Thus, Autoscore affords a practical research tool, with clinical application, for scoring listener intelligibility of speech.

Are there sex effects for speech intelligibility in American English? Examining the influence of talker, listener, and methodology.

Talker and listener sex in speech processing has been largely unknown and under-appreciated to this point, with many studies overlooking the possible influences. In the current study, the effects of both talker and listener sex on speech intelligibility were assessed. Different methodological approaches to measuring intelligibility (percent words correct vs. subjective rating scales) and collecting data (laboratory vs. crowdsourcing) were also evaluated. Findings revealed that, regardless of methodology, the spoken productions of female talkers were overall more intelligible than the spoken productions of male talkers; however, substantial variability across talkers was observed. Findings also revealed that when data were collected in the lab, there was an interaction between talker and listener sex. This interaction between listener and talker sex was not observed when subjective ratings were crowdsourced from listener subjects across the USA via Amazon Mechanical Turk, although overall ratings remained similar. This possibly suggests that subjective intelligibility ratings may be vulnerable to bias, and such biases may be reduced by recruiting a more heterogeneous subject pool. Many studies in speech perception do not account for these talker, listener, and methodology effects. However, the present results suggest that researchers should carefully consider these effects when assessing speech intelligibility in different conditions, and when comparing findings across studies that have used different subject demographics and/or methodologies.

The noise susceptibility of various speech bands.

The degrading influence of noise on various critical bands of speech was assessed. A modified version of the compound method [Apoux and Healy (2012) J. Acoust. Soc. Am. 132, 1078-1087] was employed to establish this noise susceptibility for each speech band. Noise was added to the target speech band at various signal-to-noise ratios to determine the amount of noise required to reduce the contribution of that band by 50%. It was found that noise susceptibility is not equal across the speech spectrum, as is commonly assumed and incorporated into modern indexes. Instead, the signal-to-noise ratio required to equivalently impact various speech bands differed by as much as 13 dB. This noise susceptibility formed an irregular pattern across frequency, despite the use of multi-talker speech materials designed to reduce the potential influence of a particular talker's voice. But basic trends in the pattern of noise susceptibility across the spectrum emerged. Further, no systematic relationship was observed between noise susceptibility and speech band importance. It is argued here that susceptibility to noise and band importance are different phenomena, and that this distinction may be underappreciated in previous works.

Speech-material and talker effects in speech band importance.

Band-importance functions created using the compound method [Apoux and Healy (2012). J. Acoust. Soc. Am. 132, 1078-1087] provide more detail than those generated using the ANSI technique, necessitating and allowing a re-examination of the influences of speech material and talker on the shape of the band-importance function. More specifically, the detailed functions may reflect, to a larger extent, acoustic idiosyncrasies of the individual talker's voice. Twenty-one band functions were created using standard speech materials and recordings by different talkers. The band-importance functions representing the same speech-material type produced by different talkers were found to be more similar to one another than functions representing the same talker producing different speech-material types. Thus, the primary finding was the relative strength of a speech-material effect and weakness of a talker effect. This speech-material effect extended to other materials in the same broad class (different sentence corpora) despite considerable differences in the specific materials. Characteristics of individual talkers' voices were not readily apparent in the functions, and the talker effect was restricted to more global aspects of talker (i.e., gender). Finally, the use of multiple talkers diminished any residual effect of the talker.

Combining degradations: The effect of background noise on intelligibility of disordered speech.

The effect of background noise on intelligibility of disordered speech was assessed. Speech-shaped noise was mixed with neurologically healthy (control) and disordered (dysarthric) speech at a series of signal-to-noise ratios. In addition, bandpass filtered control and dysarthric speech conditions were assessed to determine the effect of noise on both naturally and artificially degraded speech. While significant effects of both the amount of noise and the type of speech were revealed, no interaction between the two factors was observed, in either the broadband or filtered testing conditions. Thus, it appears that there is no multiplicative effect of the presence of background noise on intelligibility of disordered speech relative to control speech. That is, the decrease in intelligibility due to increasing levels of noise is similar for both types of speech, and both types of testing conditions, and the function for dysarthric speech is simply shifted downward due to the inherent source degradations of the speech itself. Last, large-scale online crowdsourcing via Amazon Mechanical Turk was utilized to collect data for the current study. Findings and implications for this data and data collection approach are discussed.

The Effect of Remote Masking on the Reception of Speech by Young School-Age Children.

Purpose: Psychoacoustic data indicate that infants and children are less likely than adults to focus on a spectral region containing an anticipated signal and are more susceptible to remote masking of a signal. These detection tasks suggest that infants and children, unlike adults, do not listen selectively. However, less is known about children's ability to listen selectively during speech recognition. Accordingly, the current study examines remote masking during speech recognition in children and adults. Method: Adults and 7- and 5-year-old children performed sentence recognition in the presence of various spectrally remote maskers. Intelligibility was determined for each remote-masker condition, and performance was compared across age groups. Results: It was found that speech recognition for 5-year-olds was reduced in the presence of spectrally remote noise, whereas the maskers had no effect on the 7-year-olds or adults. Maskers of different bandwidth and remoteness had similar effects. Conclusions: In accord with psychoacoustic data, young children do not appear to focus on a spectral region of interest and ignore other regions during speech recognition. This tendency may help account for their typically poorer speech perception in noise. This study also appears to capture an important developmental stage, during which a substantial refinement in spectral listening occurs.

Measuring time-frequency importance functions of speech with bubble noise.

Listeners can reliably perceive speech in noisy conditions, but it is not well understood what specific features of speech they use to do this. This paper introduces a data-driven framework to identify the time-frequency locations of these features. Using the same speech utterance mixed with many different noise instances, the framework is able to compute the importance of each time-frequency point in the utterance to its intelligibility. The mixtures have approximately the same global signal-to-noise ratio at each frequency, but very different recognition rates. The difference between these intelligible vs unintelligible mixtures is the alignment between the speech and spectro-temporally modulated noise, providing different combinations of "glimpses" of speech in each mixture. The current results reveal the locations of these important noise-robust phonetic features in a restricted set of syllables. Classification models trained to predict whether individual mixtures are intelligible based on the location of these glimpses can generalize to new conditions, successfully predicting the intelligibility of novel mixtures. They are able to generalize to novel noise instances, novel productions of the same word by the same talker, novel utterances of the same word spoken by different talkers, and, to some extent, novel consonants.

Large-scale training to increase speech intelligibility for hearing-impaired listeners in novel noises.

Supervised speech segregation has been recently shown to improve human speech intelligibility in noise, when trained and tested on similar noises. However, a major challenge involves the ability to generalize to entirely novel noises. Such generalization would enable hearing aid and cochlear implant users to improve speech intelligibility in unknown noisy environments. This challenge is addressed in the current study through large-scale training. Specifically, a deep neural network (DNN) was trained on 10 000 noises to estimate the ideal ratio mask, and then employed to separate sentences from completely new noises (cafeteria and babble) at several signal-to-noise ratios (SNRs). Although the DNN was trained at the fixed SNR of - 2 dB, testing using hearing-impaired listeners demonstrated that speech intelligibility increased substantially following speech segregation using the novel noises and unmatched SNR conditions of 0 dB and 5 dB. Sentence intelligibility benefit was also observed for normal-hearing listeners in most noisy conditions. The results indicate that DNN-based supervised speech segregation with large-scale training is a very promising approach for generalization to new acoustic environments.

Difficulty understanding speech in noise by the hearing impaired: underlying causes and technological solutions.

A primary complaint of hearing-impaired individuals involves poor speech understanding when background noise is present. Hearing aids and cochlear implants often allow good speech understanding in quiet backgrounds. But hearing-impaired individuals are highly noise intolerant, and existing devices are not very effective at combating background noise. As a result, speech understanding in noise is often quite poor. In accord with the significance of the problem, considerable effort has been expended toward understanding and remedying this issue. Fortunately, our understanding of the underlying issues is reasonably good. In sharp contrast, effective solutions have remained elusive. One solution that seems promising involves a single-microphone machine-learning algorithm to extract speech from background noise. Data from our group indicate that the algorithm is capable of producing vast increases in speech understanding by hearing-impaired individuals. This paper will first provide an overview of the speech-in-noise problem and outline why hearing-impaired individuals are so noise intolerant. An overview of our approach to solving this problem will follow.

Dual-carrier processing to convey temporal fine structure cues: Implications for cochlear implants.

Speech intelligibility in noise can be degraded by using vocoder processing to alter the temporal fine structure (TFS). Here it is argued that this degradation is not attributable to the loss of speech information potentially present in the TFS. Instead it is proposed that the degradation results from the loss of sound-source segregation information when two or more carriers (i.e., TFS) are substituted with only one as a consequence of vocoder processing. To demonstrate this segregation role, vocoder processing involving two carriers, one for the target and one for the background, was implemented. Because this approach does not preserve the speech TFS, it may be assumed that any improvement in intelligibility can only be a consequence of the preserved carrier duality and associated segregation cues. Three experiments were conducted using this "dual-carrier" approach. All experiments showed substantial sentence intelligibility in noise improvements compared to traditional single-carrier conditions. In several conditions, the improvement was so substantial that intelligibility approximated that for unprocessed speech in noise. A foreseeable and potentially promising implication for the dual-carrier approach involves implementation into cochlear implant speech processors, where it may provide the TFS cues necessary to segregate speech from noise.

An algorithm to increase speech intelligibility for hearing-impaired listeners in novel segments of the same noise type.

Machine learning algorithms to segregate speech from background noise hold considerable promise for alleviating limitations associated with hearing impairment. One of the most important considerations for implementing these algorithms into devices such as hearing aids and cochlear implants involves their ability to generalize to conditions not employed during the training stage. A major challenge involves the generalization to novel noise segments. In the current study, sentences were segregated from multi-talker babble and from cafeteria noise using an algorithm that employs deep neural networks to estimate the ideal ratio mask. Importantly, the algorithm was trained on segments of noise and tested using entirely novel segments of the same nonstationary noise type. Substantial sentence-intelligibility benefit was observed for hearing-impaired listeners in both noise types, despite the use of unseen noise segments during the test stage. Interestingly, normal-hearing listeners displayed benefit in babble but not in cafeteria noise. This result highlights the importance of evaluating these algorithms not only in human subjects, but in members of the actual target population.

Speech-cue transmission by an algorithm to increase consonant recognition in noise for hearing-impaired listeners.

Consonant recognition was assessed following extraction of speech from noise using a more efficient version of the speech-segregation algorithm described in Healy, Yoho, Wang, and Wang [(2013) J. Acoust. Soc. Am. 134, 3029-3038]. Substantial increases in recognition were observed following algorithm processing, which were significantly larger for hearing-impaired (HI) than for normal-hearing (NH) listeners in both speech-shaped noise and babble backgrounds. As observed previously for sentence recognition, older HI listeners having access to the algorithm performed as well or better than young NH listeners in conditions of identical noise. It was also found that the binary masks estimated by the algorithm transmitted speech features to listeners in a fashion highly similar to that of the ideal binary mask (IBM), suggesting that the algorithm is estimating the IBM with substantial accuracy. Further, the speech features associated with voicing, manner of articulation, and place of articulation were all transmitted with relative uniformity and at relatively high levels, indicating that the algorithm and the IBM transmit speech cues without obvious deficiency. Because the current implementation of the algorithm is much more efficient, it should be more amenable to real-time implementation in devices such as hearing aids and cochlear implants.

An algorithm to improve speech recognition in noise for hearing-impaired listeners.

Despite considerable effort, monaural (single-microphone) algorithms capable of increasing the intelligibility of speech in noise have remained elusive. Successful development of such an algorithm is especially important for hearing-impaired (HI) listeners, given their particular difficulty in noisy backgrounds. In the current study, an algorithm based on binary masking was developed to separate speech from noise. Unlike the ideal binary mask, which requires prior knowledge of the premixed signals, the masks used to segregate speech from noise in the current study were estimated by training the algorithm on speech not used during testing. Sentences were mixed with speech-shaped noise and with babble at various signal-to-noise ratios (SNRs). Testing using normal-hearing and HI listeners indicated that intelligibility increased following processing in all conditions. These increases were larger for HI listeners, for the modulated background, and for the least-favorable SNRs. They were also often substantial, allowing several HI listeners to improve intelligibility from scores near zero to values above 70%.

Role and relative contribution of temporal envelope and fine structure cues in sentence recognition by normal-hearing listeners.

The present study investigated the role and relative contribution of envelope and temporal fine structure (TFS) to sentence recognition in noise. Target and masker stimuli were added at five different signal-to-noise ratios (SNRs) and filtered into 30 contiguous frequency bands. The envelope and TFS were extracted from each band by Hilbert decomposition. The final stimuli consisted of the envelope of the target/masker sound mixture at x dB SNR and the TFS of the same sound mixture at y dB SNR. A first experiment showed a very limited contribution of TFS cues, indicating that sentence recognition in noise relies almost exclusively on temporal envelope cues. A second experiment showed that replacing the carrier of a sound mixture with noise (vocoder processing) cannot be considered equivalent to disrupting the TFS of the target signal by adding a background noise. Accordingly, a re-evaluation of the vocoder approach as a model to further understand the role of TFS cues in noisy situations may be necessary. Overall, these data are consistent with the view that speech information is primarily extracted from the envelope while TFS cues are primarily used to detect glimpses of the target.

Band importance for sentences and words reexamined.

Band-importance functions were created using the "compound" technique [Apoux and Healy, J. Acoust. Soc. Am. 132, 1078-1087 (2012)] that accounts for the multitude of synergistic and redundant interactions that take place among speech bands. Functions were created for standard recordings of the speech perception in noise (SPIN) sentences and the Central Institute for the Deaf (CID) W-22 words using 21 critical-band divisions and steep filtering to eliminate the influence of filter slopes. On a given trial, a band of interest was presented along with four other bands having spectral locations determined randomly on each trial. In corresponding trials, the band of interest was absent and only the four other bands were present. The importance of the band of interest was determined by the difference between paired band-present and band-absent trials. Because the locations of the other bands changed randomly from trial to trial, various interactions occurred between the band of interest and other speech bands which provided a general estimate of band importance. Obtained band-importance functions differed substantially from those currently available for identical speech recordings. In addition to differences in the overall shape of the functions, especially for the W-22 words, a complex microstructure was observed in which the importance of adjacent frequency bands often varied considerably. This microstructure may result in better predictive power of the current functions.