Eunmi Oh

A review on the computational methods for emotional state estimation from the human EEG.

A growing number of affective computing researches recently developed a computer system that can recognize an emotional state of the human user to establish affective human-computer interactions. Various measures have been used to estimate emotional states, including self-report, startle response, behavioral response, autonomic measurement, and neurophysiologic measurement. Among them, inferring emotional states from electroencephalography (EEG) has received considerable attention as EEG could directly reflect emotional states with relatively low costs and simplicity. Yet, EEG-based emotional state estimation requires well-designed computational methods to extract information from complex and noisy multichannel EEG data. In this paper, we review the computational methods that have been developed to deduct EEG indices of emotion, to extract emotion-related features, or to classify EEG signals into one of many emotional states. We also propose using sequential Bayesian inference to estimate the continuous emotional state in real time. We present current challenges for building an EEG-based emotion recognition system and suggest some future directions.  

Overview of the EVS codec architecture

The recently standardized 3GPP codec for Enhanced Voice Services (EVS) offers new features and improvements for low-delay real-time communication systems. Based on a novel, switched low-delay speech/audio codec, the EVS codec contains various tools for better compression efficiency and higher quality for clean/noisy speech, mixed content and music, including support for wideband, super-wideband and full-band content. The EVS codec operates in a broad range of bitrates, is highly robust against packet loss and provides an AMR-WB interoperable mode for compatibility with existing systems. This paper gives an overview of the underlying architecture as well as the novel technologies in the EVS codec and presents listening test results showing the performance of the new codec in terms of compression and speech/audio quality.

Bandwidth Extension for China AVS-M standard

We proposed a new frequency domain BandWidth Extension (BWE) technology. In the new technology, FFT based frequency domain gain shaping combined with Linear Prediction Coding (LPC) based spectral envelope shaping is used for generating high frequency signals. To preserve the amount of noise component in the reconstructed band, gain reduction controlled by Spectrum Flatness Measurement (SFM) is employed. Subjective testing results show that the presented technology exhibits a comparable performance compared to 3GPP AMR-WB+ with the same bit-rate in the framework of Audio Video coding of China Standard (AVS) Part 10 - Mobile Speech and Audio Codec. This technology has been formally adopted as the artificial high band coding module in AVS P10.

An efficient LSF quantization using dynamic bit allocation

The current paper is concerned with an effective method to quantize a spectrum envelope of a speech signal without having an inter-frame prediction. In this paper, we proposed a method referred to as dynamic bit allocation-split vector quantization (DBA-SVQ). The main feature of this structure is that it makes use of the ordering property of line spectral frequencies (LSF) and exploits multiple codebooks, normalization and the DBA technique. As a result, we can limit the dynamic range of LSF sub-vectors and allocate different numbers of bits in accordance with the range sizes to maximize the overall efficiency of quantization. The performance is compared with delta line spectral pairs (LSP) VQ, which is used in EVRC-B, demonstrating reduction in spectral distortion (SD).

High-quality audio transform coded excitation using trellis codes

A trellis source code and novel variable-length lossless code are used in transform coded excitation audio coding. Implemented within the extended adaptive multi-rate wideband (AMR-WB+) audio coding framework, the proposed quantization and lossless coding method provide between 0.4 and 0.7 dB increase in signal-to-noise ratio over the E8 lattice VQ and spherical lossless code used in the AMR-WB+ standard.

Improving Perceptual Quality of Speech in a Noisy Environment by Enhancing Temporal Envelope and Pitch

This letter proposes a new method of improving perceptual quality of speech in a noisy environment. Based on the perception theory that the temporal envelope plays a major role in assessing intelligibility, the proposed method uses a novel operation that enhances the fluctuation of the band-wise temporal envelope. It also contains pitch enhancement in frequency domain to further improve the perceptual quality. A new subjective evaluation scheme employing binaural listening is proposed in order to measure perceptual quality more reliably. The subjective evaluation shows that the proposed method improves perceptual quality of speech in various noisy environments.

Comparative analysis of cognitive tasks for modeling mental workload with electroencephalogram.

Previous electroencephalogram (EEG) studies have shown that cognitive workload can be estimated by using several types of cognitive tasks. In this study, we attempted to characterize cognitive tasks that have been used to manipulate workload for generating classification models. We carried out a comparative analysis between two representative types of working memory tasks: the n-back task and the mental arithmetic task. Based on experiments with 7 healthy subjects using Emotiv EPOC, we compared the consistency, robustness, and efficiency of each task in determining cognitive workload in a short training session. The mental arithmetic task seems consistent and robust in manipulating clearly separable high and low levels of cognitive workload with less training. In addition, the mental arithmetic task shows consistency despite repeated usage over time and without notable task adaptation in users. The current study successfully quantifies the quality and efficiency of cognitive workload modeling depending on the type and configuration of training tasks.

Toward realistic implementation of Brain-Computer Interface for TV channel control

In recent studies, there have been attempts to control smart devices using Brain-Computer Interface (BCI) as a proof-of-concept. BCI can be a new interface between the human brain and various consumer electronic devices. Among various BCI paradigms, we adopted P300-based BCI which has higher accuracy with less variability among subjects and requires less training. We have explored the feasibility of TV channel selection based on BCI at typical home environment in terms of viewing distance (3 meters) and screen size (46 inches). Four candidate channel menus in video type were displayed on each quadrant of TV screen. On the upper-left or upper-right corner of each rectangular channel menu, visual stimulus was flashed to elicit Event Related Potentials (ERP). With 8 subjects, we achieved 92.3% average accuracy using 16 EEG channels and 89.6% average accuracy using only 3 EEG channels positioned on the midline sites of human brain. We found an optimal subset of EEG channels while keeping the performance.

Flexible spectrum coding in the 3GPP EVS codec

This paper proposes a flexible encoding technique based on multi-stage multiple scale lattice vector quantization and block-constrained trellis coded vector quantization. It is used for the spectrum encoding, more precisely encoding of the LSF parameters, and incorporated in the recently standardized 3GPP EVS codec. The proposed method can handle multiple bit allocations and signal types with low complexity and low memory requirements.

A novel frequency domain BWE with relaxed synchronization and associated BWE switching

This paper presents a novel frequency domain bandwidth extension (BWE) scheme with relaxed synchronization, optimized for coding inactive and music/mixed content signals. The algorithm achieves high subjective quality at low and medium bitrates and it has a low algorithmic delay. The algorithm is part of the 3GPP Enhanced Voice Services (EVS) codec. In addition to the presented algorithm, the EVS codec employs also a time domain BWE scheme optimized for active speech coding. Consequently a seamless switching between these BWE technologies is required and described in this paper as well.