Vladimir Malenovsky

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.

Advances in low bitrate time-frequency coding

In this paper a novel technique is presented to efficiently mix traditional ACELP time domain coding with a frequency domain coding model to improve the quality of generic audio signals coded at low bitrates without additional delay. The paper discusses how to integrate parts of a traditional Algebraic Code Excited Linear Prediction (ACELP) speech codec to create a time-domain contribution which coexists with a frequency based coding model. A mechanism to determine the value of the time-domain contribution is proposed and a method is described how the frequency-domain contribution might be added without increasing the overall delay of the codec. The proposed method forms part of the recently standardised 3GPP EVS codec.

Two-stage speech/music classifier with decision smoothing and sharpening in the EVS codec

In most internationally recognized standardized multi-mode codecs, signal classification is performed in a single step by either linear discrimination or SNR-based metrics. The speech/music classifier of the EVS codec achieves greater discrimination than these single-step models by combining Gaussian mixture modelling (GMM) with a series of context-based improvement layers. Additionally, unlike traditional GMM classifiers the EVS model adopts a short hangover period, allowing it to track transitions between music and speech. Misclassifications are mitigated by applying a novel decision smoothing and sharpening technique. The results in relatively static environments demonstrate that the new two-stage approach with selective hangover leads to classification accuracies comparable to speech/music classifiers with longer hangovers. They also show that the new approach leads to faster and more accurate switching of coding modes than conventional classifiers for more complex audio environments such as advertisements, jingles and speech superimposed on music.

Inter-tone noise reduction in a low bit rate CELP decoder

In this paper we present a novel technique to enhance music signals encoded using a low bit rate CELP coder. The method is based on reduction of inter-tone quantization noise for decoded music signals without affecting the quality for speech signals. The proposed technique consists of two modules. The first module is used to discriminate between stable tonal sounds and other sounds and the second module is used to reduce the inter-tone quantization noise in the stable tonal segments. The inter-tone noise is reduced by means of spectral subtraction. The proposed method is a part of the newly standardised ITU-T G.718 codec.

Memory-less gain quantization in the EVS codec

The recent standard on Enhanced Voiced Services (EVS) contains two memory-less gain coding mechanisms achieving better performance than the prediction-based techniques used in 3GPP AMR-WB and ITU-T G.729 codecs. The EVS gain encoder uses joint vector quantization without the need of information from previous frames. Inter-frame prediction is replaced by alternative schemes based on sub-frame prediction or estimated average target signal energy. This eliminates the propagation of error inside the adaptive codebook and reduces the risk of artifacts in the recovery stage after frame error concealment. The results show that the EVS codec outperforms AMR-WB at all bitrates while keeping the same amount of bits required for gain quantization.