Neural tracking of the speech envelope predicts binaural unmasking.

Binaural unmasking is a remarkable phenomenon that it is substantially easier to detect a signal in noise when the interaural parameters of the signal are different from those of the noise - a useful mechanism in so-called cocktail party scenarios. In this study, we investigated the effect of binaural unmasking on neural tracking of the speech envelope. We measured EEG in 8 participants who listened to speech in noise at a fixed signal-to-noise ratio, in two conditions: one where speech and noise had the same interaural phase difference (both speech and noise having an opposite waveform across ears, SπNπ), and one where the interaural phase difference of the speech was different from that of the noise (only the speech having an opposite waveform across ears, SπN).

Classifying coherent versus nonsense speech perception from EEG using linguistic speech features.

When a person listens to natural speech, the relation between features of the speech signal and the corresponding evoked electroencephalogram (EEG) is indicative of neural processing of the speech signal. Using linguistic representations of speech, we investigate the differences in neural processing between speech in a native and foreign language that is not understood. We conducted experiments using three stimuli: a comprehensible language, an incomprehensible language, and randomly shuffled words from a comprehensible language, while recording the EEG signal of native Dutch-speaking participants.

Auditory Steady-State Responses: Multiplexed Amplitude Modulation Frequencies to Reduce Recording Time.

Objectives: This study investigated the efficiency of a multiplexed amplitude-modulated (AM) stimulus in eliciting auditory steady-state responses. The multiplexed AM stimulus was created by simultaneously modulating speech-shaped noise with three frequencies chosen to elicit different neural generators: 3.1, 40.

Exploring neural tracking of acoustic and linguistic speech representations in individuals with post-stroke aphasia.

Aphasia is a communication disorder that affects processing of language at different levels (e.g., acoustic, phonological, semantic).

The role of vowel and consonant onsets in neural tracking of natural speech.

. To investigate how the auditory system processes natural speech, models have been created to relate the electroencephalography (EEG) signal of a person listening to speech to various representations of the speech. Mainly the speech envelope has been used, but also phonetic representations.

Robust neural tracking of linguistic speech representations using a convolutional neural network.

When listening to continuous speech, populations of neurons in the brain track different features of the signal. Neural tracking can be measured by relating the electroencephalography (EEG) and the speech signal. Recent studies have shown a significant contribution of linguistic features over acoustic neural tracking using linear models.

Heard or Understood? Neural Tracking of Language Features in a Comprehensible Story, an Incomprehensible Story and a Word List.

Speech comprehension is a complex neural process on which relies on activation and integration of multiple brain regions. In the current study, we evaluated whether speech comprehension can be investigated by neural tracking. Neural tracking is the phenomenon in which the brain responses time-lock to the rhythm of specific features in continuous speech.

Relating EEG to continuous speech using deep neural networks: a review.

When a person listens to continuous speech, a corresponding response is elicited in the brain and can be recorded using electroencephalography (EEG). Linear models are presently used to relate the EEG recording to the corresponding speech signal. The ability of linear models to find a mapping between these two signals is used as a measure of neural tracking of speech.

Beyond linear neural envelope tracking: a mutual information approach.

The human brain tracks the temporal envelope of speech, which contains essential cues for speech understanding. Linear models are the most common tool to study neural envelope tracking. However, information on how speech is processed can be lost since nonlinear relations are precluded.

Decoding of the speech envelope from EEG using the VLAAI deep neural network.

To investigate the processing of speech in the brain, commonly simple linear models are used to establish a relationship between brain signals and speech features. However, these linear models are ill-equipped to model a highly-dynamic, complex non-linear system like the brain, and they often require a substantial amount of subject-specific training data. This work introduces a novel speech decoder architecture: the Very Large Augmented Auditory Inference (VLAAI) network.

Neural tracking as a diagnostic tool to assess the auditory pathway.

When a person listens to sound, the brain time-locks to specific aspects of the sound. This is called neural tracking and it can be investigated by analysing neural responses (e.g.

Speech Understanding Oppositely Affects Acoustic and Linguistic Neural Tracking in a Speech Rate Manipulation Paradigm.

When listening to continuous speech, the human brain can track features of the presented speech signal. It has been shown that neural tracking of acoustic features is a prerequisite for speech understanding and can predict speech understanding in controlled circumstances. However, the brain also tracks linguistic features of speech, which may be more directly related to speech understanding.

Hearing loss is associated with delayed neural responses to continuous speech.

We investigated the impact of hearing loss on the neural processing of speech. Using a forward modelling approach, we compared the neural responses to continuous speech of 14 adults with sensorineural hearing loss with those of age-matched normal-hearing peers. Compared with their normal-hearing peers, hearing-impaired listeners had increased neural tracking and delayed neural responses to continuous speech in quiet.

Neural Markers of Speech Comprehension: Measuring EEG Tracking of Linguistic Speech Representations, Controlling the Speech Acoustics.

When listening to speech, our brain responses time lock to acoustic events in the stimulus. Recent studies have also reported that cortical responses track linguistic representations of speech. However, tracking of these representations is often described without controlling for acoustic properties.

Effect of number and placement of EEG electrodes on measurement of neural tracking of speech.

Measurement of neural tracking of natural running speech from the electroencephalogram (EEG) is an increasingly popular method in auditory neuroscience and has applications in audiology. The method involves decoding the envelope of the speech signal from the EEG signal, and calculating the correlation with the envelope of the audio stream that was presented to the subject. Typically EEG systems with 64 or more electrodes are used.

The effect of stimulus intensity on neural envelope tracking.

Objectives In recent years, there has been significant interest in recovering the temporal envelope of a speech signal from the neural response to investigate neural speech processing. The research focus is now broadening from neural speech processing in normal-hearing listeners towards hearing-impaired listeners. When testing hearing-impaired listeners, speech has to be amplified to resemble the effect of a hearing aid and compensate for peripheral hearing loss.

The Effect of Stimulus Choice on an EEG-Based Objective Measure of Speech Intelligibility.

Objectives: Recently, an objective measure of speech intelligibility (SI), based on brain responses derived from the electroencephalogram (EEG), has been developed using isolated Matrix sentences as a stimulus. We investigated whether this objective measure of SI can also be used with natural speech as a stimulus, as this would be beneficial for clinical applications.

Design: We recorded the EEG in 19 normal-hearing participants while they listened to two types of stimuli: Matrix sentences and a natural story.

Hearing impairment is associated with enhanced neural tracking of the speech envelope.

Elevated hearing thresholds in hearing impaired adults are usually compensated by providing amplification through a hearing aid. In spite of restoring hearing sensitivity, difficulties with understanding speech in noisy environments often remain. One main reason is that sensorineural hearing loss not only causes loss of audibility but also other deficits, including peripheral distortion but also central temporal processing deficits.

Top-down modulation of neural envelope tracking: The interplay with behavioral, self-report and neural measures of listening effort.

When listening to natural speech, our brain activity tracks the slow amplitude modulations of speech, also called the speech envelope. Moreover, recent research has demonstrated that this neural envelope tracking can be affected by top-down processes. The present study was designed to examine if neural envelope tracking is modulated by the effort that a person expends during listening.

Effect of Task and Attention on Neural Tracking of Speech.

EEG-based measures of neural tracking of natural running speech are becoming increasingly popular to investigate neural processing of speech and have applications in audiology. When the stimulus is a single speaker, it is usually assumed that the listener actively attends to and understands the stimulus. However, as the level of attention of the listener is inherently variable, we investigated how this affected neural envelope tracking.

Stimulus-aware spatial filtering for single-trial neural response and temporal response function estimation in high-density EEG with applications in auditory research.

A common problem in neural recordings is the low signal-to-noise ratio (SNR), particularly when using non-invasive techniques like magneto- or electroencephalography (M/EEG). To address this problem, experimental designs often include repeated trials, which are then averaged to improve the SNR or to infer statistics that can be used in the design of a denoising spatial filter. However, collecting enough repeated trials is often impractical and even impossible in some paradigms, while analyses on existing data sets may be hampered when these do not contain such repeated trials.

Evidence for enhanced neural tracking of the speech envelope underlying age-related speech-in-noise difficulties.

When we grow older, understanding speech in noise becomes more challenging. Research has demonstrated the role of auditory temporal and cognitive deficits in these age-related speech-in-noise difficulties. To better understand the underlying neural mechanisms, we recruited young, middle-aged, and older normal-hearing adults and investigated the interplay between speech understanding, cognition, and neural tracking of the speech envelope using electroencephalography.

Speech Intelligibility Predicted from Neural Entrainment of the Speech Envelope.

Speech intelligibility is currently measured by scoring how well a person can identify a speech signal. The results of such behavioral measures reflect neural processing of the speech signal, but are also influenced by language processing, motivation, and memory. Very often, electrophysiological measures of hearing give insight in the neural processing of sound.

APEX/SPIN: a free test platform to measure speech intelligibility.

Objectives: Measuring speech intelligibility in quiet and noise is important in clinical practice and research. An easy-to-use free software platform for conducting speech tests is presented, called APEX/SPIN.

Design: The APEX/SPIN platform allows the use of any speech material in combination with any noise.

Comparison of speech envelope extraction methods for EEG-based auditory attention detection in a cocktail party scenario.

Recent research has shown that it is possible to detect which of two simultaneous speakers a person is attending to, using brain recordings and the temporal envelope of the separate speech signals. However, a wide range of possible methods for extracting this speech envelope exists. This paper assesses the effect of different envelope extraction methods with varying degrees of auditory modelling on the performance of auditory attention detection (AAD), and more specifically on the detection accuracy.