The listening talker: A review of human and algorithmic context-induced modifications of speech

International audienceSpeech output technology is finding widespread application, including in scenarios where intelligibility might be compromised - at least for some listeners - by adverse conditions. Unlike most current algorithms, talkers continually adapt their speech patterns as a response to the immediate context of spoken communication, where the type of interlocutor and the environment are the dominant situational factors influencing speech production. Observations of talker behaviour can motivate the design of more robust speech output algorithms. Starting with a listener-oriented categorisation of possible goals for speech modification, this review article summarises the extensive set of behavioural findings related to human speech modification, identifies which factors appear to be beneficial, and goes on to examine previous computational attempts to improve intelligibility in noise. The review concludes by tabulating 46 speech modifications, many of which have yet to be perceptually or algorithmically evaluated. Consequently, the review provides a roadmap for future work in improving the robustness of speech output

Real-Time Contrast Enhancement to Improve Speech Recognition

An algorithm that operates in real-time to enhance the salient features of speech is described and its efficacy is evaluated. The Contrast Enhancement (CE) algorithm implements dynamic compressive gain and lateral inhibitory sidebands across channels in a modified winner-take-all circuit, which together produce a form of suppression that sharpens the dynamic spectrum. Normal-hearing listeners identified spectrally smeared consonants (VCVs) and vowels (hVds) in quiet and in noise. Consonant and vowel identification, especially in noise, were improved by the processing. The amount of improvement did not depend on the degree of spectral smearing or talker characteristics. For consonants, when results were analyzed according to phonetic feature, the most consistent improvement was for place of articulation. This is encouraging for hearing aid applications because confusions between consonants differing in place are a persistent problem for listeners with sensorineural hearing loss

The effects of auditory contrast tuning upon speech intelligibility

We have previously identified neurons tuned to spectral contrast of wideband sounds in auditory cortex of awake marmoset monkeys. Because additive noise alters the spectral contrast of speech, contrast-tuned neurons, if present in human auditory cortex, may aid in extracting speech from noise. Given that this cortical function may be underdeveloped in individuals with sensorineural hearing loss, incorporating biologically-inspired algorithms into external signal processing devices could provide speech enhancement benefits to cochlear implantees. In this study we first constructed a computational signal processing algorithm to mimic auditory cortex contrast tuning. We then manipulated the shape of contrast channels and evaluated the intelligibility of reconstructed noisy speech using a metric to predict cochlear implant user perception. Candidate speech enhancement strategies were then tested in cochlear implantees with a hearing-in-noise test. Accentuation of intermediate contrast values or all contrast values improved computed intelligibility. Cochlear implant subjects showed significant improvement in noisy speech intelligibility with a contrast shaping procedure

Objective measures for predicting the intelligibility of spectrally smoothed speech with artificial excitation

A study is presented on how well objective measures of speech quality and intelligibility can predict the subjective in- telligibility of speech that has undergone spectral envelope smoothing and simplification of its excitation. Speech modi- fications are made by resynthesising speech that has been spec- trally smoothed. Objective measures are applied to the mod- ified speech and include measures of speech quality, signal- to-noise ratio and intelligibility, as well as proposing the nor- malised frequency-weighted spectral distortion (NFD) measure. The measures are compared to subjective intelligibility scores where it is found that several have high correlation (|r| ≥ 0.7), with NFD achieving the highest correlation (r = −0.81

Effects of Expanding Envelope Fluctuations on Consonant Perception in Hearing-Impaired Listeners

This study examined the perceptual consequences of three speech enhancement schemes based on multiband nonlinear expansion of temporal envelope fluctuations between 10 and 20 Hz: (a) “idealized” envelope expansion of the speech before the addition of stationary background noise, (b) envelope expansion of the noisy speech, and (c) envelope expansion of only those time-frequency segments of the noisy speech that exhibited signal-to-noise ratios (SNRs) above −10 dB. Linear processing was considered as a reference condition. The performance was evaluated by measuring consonant recognition and consonant confusions in normal-hearing and hearing-impaired listeners using consonant-vowel nonsense syllables presented in background noise. Envelope expansion of the noisy speech showed no significant effect on the overall consonant recognition performance relative to linear processing. In contrast, SNR-based envelope expansion of the noisy speech improved the overall consonant recognition performance equivalent to a 1- to 2-dB improvement in SNR, mainly by improving the recognition of some of the stop consonants. The effect of the SNR-based envelope expansion was similar to the effect of envelope-expanding the clean speech before the addition of noise

Evaluation of the sparse coding shrinkage noise reduction algorithm for the hearing impaired

Although there are numerous single-channel noise reduction strategies to improve speech perception in a noisy environment, most of them can only improve speech quality but not improve speech intelligibility for normal hearing (NH) or hearing impaired (HI) listeners. Exceptions that can improve speech intelligibility currently are only those that require a priori statistics of speech or noise. Most of the noise reduction algorithms in hearing aids are adopted directly from the algorithms for NH listeners without taking into account of the hearing loss factors within HI listeners. HI listeners suffer more in speech intelligibility than NH listeners in the same noisy environment. Further study of monaural noise reduction algorithms for HI listeners is required.The motivation is to adapt a model-based approach in contrast to the conventional Wiener filtering approach. The model-based algorithm called sparse coding shrinkage (SCS) was proposed to extract key speech information from noisy speech. The SCS algorithm was evaluated by comparison with another state-of-the-art Wiener filtering approach through speech intelligibility and quality tests using 9 NH and 9 HI listeners. The SCS algorithm matched the performance of the Wiener filtering algorithm in speech intelligibility and speech quality. Both algorithms showed some intelligibility improvements for HI listeners but not at all for NH listeners. The algorithms improved speech quality for both HI and NH listeners.Additionally, a physiologically-inspired hearing loss simulation (HLS) model was developed to characterize hearing loss factors and simulate hearing loss consequences. A methodology was proposed to evaluate signal processing strategies for HI listeners with the proposed HLS model and NH subjects. The corresponding experiment was performed by asking NH subjects to listen to unprocessed/enhanced speech with the HLS model. Some of the effects of the algorithms seen in HI listeners are reproduced, at least qualitatively, by using the HLS model with NH listeners.Conclusions: The model-based algorithm SCS is promising for improving performance in stationary noise although no clear difference was seen in the performance of SCS and a competitive Wiener filtering algorithm. Fluctuating noise is more difficult to reduce compared to stationary noise. Noise reduction algorithms may perform better at higher input signal-to-noise ratios (SNRs) where HI listeners can get benefit but where NH listeners already reach ceiling performance. The proposed HLS model can save time and cost when evaluating noise reduction algorithms for HI listeners

Do children enhance phonetic contrasts in speech directed to a hearing-impaired peer?

This study examines whether normal-hearing (NH) children enhance phonetic contrasts when speaking to a hearing-impaired (HI) peer. A problem-solving ‘Grid’ task was developed to elicit frequent repetitions of /p/-/b/, /s/-/S/ and /i/-/I/ segmental contrasts and point vowels in communicative spontaneous speech. Eighteen NH children between 9 and 15 years old performed the task once with a NH friend and once with a HI friend. Both category means and within-speaker variability were analysed. Results suggest that although HI interlocutors are likely to find the phonetic contrasts difficult to produce and perceive, children’s HI-directed speech contains little evidence of phonetic category enhancement