Improving perceptual coding of narrowband audio signals at low rates

Abstract

New applications such as Internet broadcast and communications, consumer multimedia products, digital AM broadcast and satellite networks are emerging. Those applications require moderate audio quality without annoying artifacts at bit rates below 16 kbit/s. Although speech coders provide high speech quality at bit rates around 8 kbit/s, they perform poorly when encoding audio signals. In this thesis, we present a novel transform coding paradigm based on the characteristics of the human hearing system. The proposed encoder, i.e., Narrowband Perceptual Audio Coder (NPAC), can accommodate a wide range of narrowband audio inputs without annoying artifacts at bit rates down to 8 kbit/s.NPAC employs a variety of algorithms to remove the perceptually irrelevant parts and statistical redundancies of the input signal. The new algorithms used in NPAC include a perceptual error measure in training the codebooks and selecting the best codewords, perceptually-based bit allocation algorithms and an adaptive predictive scheme to vector quantize the scale factors.The proposed encoder has moderate complexity and delivers good quality for narrowband audio inputs at around 1 bit/sample. Informal subjective tests have been conducted to compare the performance of NPAC with an 8 kbit/s commercially-available audio coder.The tests results show that NPAC performs better for both music and speech inputs. iii RésuméDes nouvelles technologies telles que la diffusion par Internet, la diffusion AM numérique, et les réseaux satellites deviennent de plus en plus populaires et constituent la base de plusieurs nouvelles applications et produits multimédias. La réussite de ces produits sur la marché dépend de la qualité des signaux audio et vidéo ainsi que de la largeur de bande utilisée. Pour le signal audio, il est désirable que le débit soit en bas de 16 kbit/s tout en offrant une qualité acceptable, c'est-à-dire sans de distorsion remarquable.Il està noter que certains codeurs de parole permettent de transmettre le signal de parole au débit de 8 kbit/s avec une très bonne qualité. Toutefois, puisque ces codeurs profitent de la structure particulière de la parole, ils ne peuvent pas offrir la même qualité audio pour d'autres signaux comme la musique.Dans cette thèse, nous présentons une philosophie d'encodage des signaux audio qui tient compte de la structure du système auditif. Le codeur proposé se nomme Codeur Audio Perceptuelà bandeÉtroite (CAPE). CAPE permet d'encoder plusieurs types de signal audioà bandeétroite au débit de 8 kbit/s sans de distorsion remarquable.Plusieurs nouveaux algorithmes sont utilisés dans CAPE afins d'éliminer la redondance statistique ainsi que la partie sans importance perceptuel du signal d'entrée. Parmi les nouveautés de CAPE, il y a une mesure d'erreur perceptuelle qui est utilisée lors de l'entraînement des tableaux de quantification, et pour la sélection du meilleur vecteur de ces tableaux lors de l'encodage. De plus, l'allocation des bits pour les gains du spectre dans différentes bandes de fréque...

A trellis-based optimal parameter value selection for audio coding

“…The psychoacoustic model is taken from [2] and [9] with minor modifications and simplifications. The spreading function and the prediction to find the tonality factor were derived from [17] and applied to the MDCT coefficients as described in the cited reference. For the test set, eight audio files of sampling rate 44.1 kHz were taken from the EBU SQAM [32] database, which included tonal signals, castanets, two singing files and two speech files.…”

“…Hence, the NMR values obtained from the various critical bands are combined into a scalar distortion metric. Two common metrics are: ANMR, which is the NMR averaged over all the critical bands in the frame, and MNMR, which is the maximum NMR of all the critical bands in a frame [17], [18].…”

“…ANMR is given by (1) and MNMR by (2) Subjective listening tests performed by us [36] and in [17] and [18] indicate substantial differences in the quality of audio signal resulting from optimization of the two metrics. At low rates, optimization of MNMR metric resulted in fewer annoying artifacts such as clicks, but the average quality was perceived to be inferior to ANMR.…”

“…However, these assumptions fail to hold in practical audio coding. In fact, subjective tests [17], [18], [36] indicate that in practice (when the above assumptions do not hold) the perceived output quality of the optimum solution for the two measures differ significantly, especially at low rates. The goal of efficient audio compression makes it imperative to optimize a correctly chosen distortion metric.…”

“…Instead, we define the optimal path through a trellis as the one that minimizes the rate (and purposely ignore the distortion for the moment). We hence redefine the cost function as the total rate function (17) Since the usual observations about additivity hold for the total rate, a dynamic programming procedure can be applied to find the optimal path for the given trellis. The optimal path gives the best rate possible while ignoring the distortion incurred.…”