Enhancement of speech intelligibility in reverberant rooms: role of amplitude envelope and temporal fine structure.
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ABSTRACT:
SUBMITTER: Srinivasan NK
PROVIDER: S-EPMC4032445 | biostudies-other | 2014 Jun
REPOSITORIES: biostudies-other
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Project description:Envelope (E) and temporal fine structure (TFS) are important features of acoustic signals and their corresponding perceptual function has been investigated with various listening tasks. To further understand the underlying neural processing of TFS, experiments in humans and animals were conducted to demonstrate the effects of modifying the TFS in natural speech sentences on both speech recognition and neural coding. The TFS of natural speech sentences was modified by distorting the phase and maintaining the magnitude. Speech intelligibility was then tested for normal-hearing listeners using the intact and reconstructed sentences presented in quiet and against background noise. Sentences with modified TFS were then used to evoke neural activity in auditory neurons of the inferior colliculus in guinea pigs. Our study demonstrated that speech intelligibility in humans relied on the periodic cues of speech TFS in both quiet and noisy listening conditions. Furthermore, recordings of neural activity from the guinea pig inferior colliculus have shown that individual auditory neurons exhibit phase locking patterns to the periodic cues of speech TFS that disappear when reconstructed sounds do not show periodic patterns anymore. Thus, the periodic cues of TFS are essential for speech intelligibility and are encoded in auditory neurons by phase locking.
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Project description:Speech signals are degraded in real-life environments, as a product of background noise or other factors. The processing of such signals for voice recognition and voice analysis systems presents important challenges. One of the conditions that make adverse quality difficult to handle in those systems is reverberation, produced by sound wave reflections that travel from the source to the microphone in multiple directions. To enhance signals in such adverse conditions, several deep learning-based methods have been proposed and proven to be effective. Recently, recurrent neural networks, especially those with long short-term memory (LSTM), have presented surprising results in tasks related to time-dependent processing of signals, such as speech. One of the most challenging aspects of LSTM networks is the high computational cost of the training procedure, which has limited extended experimentation in several cases. In this work, we present a proposal to evaluate the hybrid models of neural networks to learn different reverberation conditions without any previous information. The results show that some combinations of LSTM and perceptron layers produce good results in comparison to those from pure LSTM networks, given a fixed number of layers. The evaluation was made based on quality measurements of the signal's spectrum, the training time of the networks, and statistical validation of results. In total, 120 artificial neural networks of eight different types were trained and compared. The results help to affirm the fact that hybrid networks represent an important solution for speech signal enhancement, given that reduction in training time is on the order of 30%, in processes that can normally take several days or weeks, depending on the amount of data. The results also present advantages in efficiency, but without a significant drop in quality.
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Project description:PurposeThe purpose of this study was to examine the effects of varying wide dynamic range compression (WDRC) release time on intelligibility and clarity of reverberant speech. The study also considered the role of individual working memory.MethodThirty older listeners with mild to moderately-severe sloping sensorineural hearing loss participated. Individuals were divided into high and low working memory groups on the basis of the results of a reading span test. Participants listened binaurally to sentence stimuli simulated at a range of reverberation conditions and WDRC release times using a high compression ratio. Outcome measures included objective intelligibility and subjective clarity ratings.ResultsSpeech intelligibility and clarity ratings both decreased as a function of reverberation. The low working memory group demonstrated a greater decrease in intelligibility with increasing amounts of reverberation than the high working memory group. Both groups, regardless of working memory, had higher speech intelligibility and clarity ratings with longer WDRC release times. WDRC release time had a larger effect on speech intelligibility under more reverberant conditions.ConclusionsReverberation significantly affects speech intelligibility, particularly for individuals with lower working memory. In addition, longer release times in hearing aids may improve listener speech intelligibility and clarity in reverberant environments.
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Project description:Our acoustic environment contains a plethora of complex sounds that are often in motion. To gauge approaching danger and communicate effectively, listeners need to localize and identify sounds, which includes determining sound motion. This study addresses which acoustic cues impact listeners' ability to determine sound motion. Signal envelope (ENV) cues are implicated in both sound motion tracking and stimulus intelligibility, suggesting that these processes could be competing for sound processing resources. We created auditory chimaera from speech and noise stimuli and varied the number of frequency bands, effectively manipulating speech intelligibility. Normal-hearing adults were presented with stationary or moving chimaeras and reported perceived sound motion and content. Results show that sensitivity to sound motion is not affected by speech intelligibility, but shows a clear difference for original noise and speech stimuli. Further, acoustic chimaera with speech-like ENVs which had intelligible content induced a strong bias in listeners to report sounds as stationary. Increasing stimulus intelligibility systematically increased that bias and removing intelligible content reduced it, suggesting that sound content may be prioritized over sound motion. These findings suggest that sound motion processing in the auditory system can be biased by acoustic parameters related to speech intelligibility.
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Project description:Speech understanding in noisy environments is still one of the major challenges for cochlear implant (CI) users in everyday life. We evaluated a speech enhancement algorithm based on neural networks (NNSE) for improving speech intelligibility in noise for CI users. The algorithm decomposes the noisy speech signal into time-frequency units, extracts a set of auditory-inspired features and feeds them to the neural network to produce an estimation of which frequency channels contain more perceptually important information (higher signal-to-noise ratio, SNR). This estimate is used to attenuate noise-dominated and retain speech-dominated CI channels for electrical stimulation, as in traditional n-of-m CI coding strategies. The proposed algorithm was evaluated by measuring the speech-in-noise performance of 14 CI users using three types of background noise. Two NNSE algorithms were compared: a speaker-dependent algorithm, that was trained on the target speaker used for testing, and a speaker-independent algorithm, that was trained on different speakers. Significant improvements in the intelligibility of speech in stationary and fluctuating noises were found relative to the unprocessed condition for the speaker-dependent algorithm in all noise types and for the speaker-independent algorithm in 2 out of 3 noise types. The NNSE algorithms used noise-specific neural networks that generalized to novel segments of the same noise type and worked over a range of SNRs. The proposed algorithm has the potential to improve the intelligibility of speech in noise for CI users while meeting the requirements of low computational complexity and processing delay for application in CI devices.
| S-EPMC5256482 | biostudies-literature
Project description:The speech signal contains many acoustic properties that may contribute differently to spoken word recognition. Previous studies have demonstrated that the importance of properties present during consonants or vowels is dependent upon the linguistic context (i.e., words versus sentences). The current study investigated three potentially informative acoustic properties that are present during consonants and vowels for monosyllabic words and sentences. Natural variations in fundamental frequency were either flattened or removed. The speech envelope and temporal fine structure were also investigated by limiting the availability of these cues via noisy signal extraction. Thus, this study investigated the contribution of these acoustic properties, present during either consonants or vowels, to overall word and sentence intelligibility. Results demonstrated that all processing conditions displayed better performance for vowel-only sentences. Greater performance with vowel-only sentences remained, despite removing dynamic cues of the fundamental frequency. Word and sentence comparisons suggest that the speech envelope may be at least partially responsible for additional vowel contributions in sentences. Results suggest that speech information transmitted by the envelope is responsible, in part, for greater vowel contributions in sentences, but is not predictive for isolated words.
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Project description:There is much debate on how the spectrotemporal modulations of speech (or its spectrogram) are encoded in the responses of the auditory nerve, and whether speech intelligibility is best conveyed via the "envelope" (E) or "temporal fine-structure" (TFS) of the neural responses. Wide use of vocoders to resolve this question has commonly assumed that manipulating the amplitude-modulation and frequency-modulation components of the vocoded signal alters the relative importance of E or TFS encoding on the nerve, thus facilitating assessment of their relative importance to intelligibility. Here we argue that this assumption is incorrect, and that the vocoder approach is ineffective in differentially altering the neural E and TFS. In fact, we demonstrate using a simplified model of early auditory processing that both neural E and TFS encode the speech spectrogram with constant and comparable relative effectiveness regardless of the vocoder manipulations. However, we also show that neural TFS cues are less vulnerable than their E counterparts under severe noisy conditions, and hence should play a more prominent role in cochlear stimulation strategies.
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Project description:When acquiring language, young children may use acoustic spectro-temporal patterns in speech to derive phonological units in spoken language (e.g., prosodic stress patterns, syllables, phonemes). Children appear to learn acoustic-phonological mappings rapidly, without direct instruction, yet the underlying developmental mechanisms remain unclear. Across different languages, a relationship between amplitude envelope sensitivity and phonological development has been found, suggesting that children may make use of amplitude modulation (AM) patterns within the envelope to develop a phonological system. Here we present the Spectral Amplitude Modulation Phase Hierarchy (S-AMPH) model, a set of algorithms for deriving the dominant AM patterns in child-directed speech (CDS). Using Principal Components Analysis, we show that rhythmic CDS contains an AM hierarchy comprising 3 core modulation timescales. These timescales correspond to key phonological units: prosodic stress (Stress AM, ~2 Hz), syllables (Syllable AM, ~5 Hz) and onset-rime units (Phoneme AM, ~20 Hz). We argue that these AM patterns could in principle be used by naïve listeners to compute acoustic-phonological mappings without lexical knowledge. We then demonstrate that the modulation statistics within this AM hierarchy indeed parse the speech signal into a primitive hierarchically-organised phonological system comprising stress feet (proto-words), syllables and onset-rime units. We apply the S-AMPH model to two other CDS corpora, one spontaneous and one deliberately-timed. The model accurately identified 72-82% (freely-read CDS) and 90-98% (rhythmically-regular CDS) stress patterns, syllables and onset-rime units. This in-principle demonstration that primitive phonology can be extracted from speech AMs is termed Acoustic-Emergent Phonology (AEP) theory. AEP theory provides a set of methods for examining how early phonological development is shaped by the temporal modulation structure of speech across languages. The S-AMPH model reveals a crucial developmental role for stress feet (AMs ~2 Hz). Stress feet underpin different linguistic rhythm typologies, and speech rhythm underpins language acquisition by infants in all languages.
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Project description:The majority of psychoacoustic research investigating sound localization has utilized stationary sources, yet most naturally occurring sounds are in motion, either because the sound source itself moves, or the listener does. In normal hearing (NH) listeners, previous research showed the extent to which sound duration and velocity impact the ability of listeners to detect sound movement. By contrast, little is known about how listeners with hearing impairments perceive moving sounds; the only study to date comparing the performance of NH and bilateral cochlear implant (BiCI) listeners has demonstrated significantly poorer performance on motion detection tasks in BiCI listeners. Cochlear implants, auditory protheses offered to profoundly deaf individuals for access to spoken language, retain the signal envelope (ENV), while discarding temporal fine structure (TFS) of the original acoustic input. As a result, BiCI users do not have access to low-frequency TFS cues, which have previously been shown to be crucial for sound localization in NH listeners. Instead, BiCI listeners seem to rely on ENV cues for sound localization, especially level cues. Given that NH and BiCI listeners differentially utilize ENV and TFS information, the present study aimed to investigate the usefulness of these cues for auditory motion perception. We created acoustic chimaera stimuli, which allowed us to test the relative contributions of ENV and TFS to auditory motion perception. Stimuli were either moving or stationary, presented to NH listeners in free field. The task was to track the perceived sound location. We found that removing low-frequency TFS reduces sensitivity to sound motion, and fluctuating speech envelopes strongly biased the judgment of sounds to be stationary. Our findings yield a possible explanation as to why BiCI users struggle to identify sound motion, and provide a first account of cues important to the functional aspect of auditory motion perception.
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