Various studies have shown that the instrumental measures wideband PESQ and POLQA are not reliably predicting speech quality for artificial speech bandwidth extension (ABE) test conditions, as this has never been their scope. Based on data from a coordinated subjective listening test with 12 ABE variants developed by 6 different institutions, conducted in 4 languages, we propose in this work a novel instrumental quality measure that is specifically suited for narrowband-to-wideband ABE test conditions. In particular, our contributions are fourfold: First, we propose quality indicators particularly being able to detect ABE-related distortions. Second, we investigate the combination of perceptually and nonperceptually motivated distortion-related statistics. Third, we propose a support-vector-machine-based high-performance MOS predictor for ABE speech quality assessment, finally, we present the training process based on the subjective listening test data. A k-fold cross-validation test on 1) disjoint languages, 2) disjoint speakers, and 3) disjoint ABE solutions proves the superiority of our proposed measure in the ITU-T-recommended categories accuracy, consistency, and linearity compared to both, wideband PESQ and POLQA.

In studies on artificial bandwidth extension (ABE), there is a lack of international coordination in subjective tests between multiple methods and languages. Here we present the design of absolute category rating listening tests evaluating 12 ABE variants of six approaches in multiple languages, namely in American English, Chinese, German, and Korean. Since the number of ABE variants caused a higher-than-recommended length of the listening test, ABE variants were distributed into two separate listening tests per language. The paper focuses on the listening test design, which aimed at merging the subjective scores of both tests and thus allows for a joint analysis of all ABE variants under test at once. A language-dependent analysis, evaluating ABE variants in the context of the underlying coded narrowband speech condition showed statistical significant improvement in English, German, and Korean for some ABE solutions.

During the transition to wideband speech telephony, artificial bandwidth extension (ABE) could help to preserve customer satisfaction by enhancing speech quality in case of narrowband (NB) calls. However, the assessment of speech quality for ABE systems is still an open question. In the literature, instrumental measures are often used to judge the quality of ABE solutions. When subjective listening tests are considered, they most often use a comparison category rating (CCR) scale and, more rarely, an absolute category rating (ACR) scale. This paper investigates the relevance of instrumental and subjective assessment methods for ABE systems. An ACR and a CCR test are organized. Their results are compared and discussed. Discrepancies between these two tests open the discussion for the design of a proper subjective listening test for ABE systems. Some instrumental measures are also evaluated. A poor correlation between these measures and the subjective results is observed.

Recommendation G.729.1 is a new ITU-T standard which was approved in May 2006. This recommendation describes a hierarchical speech and audio coding algorithm built on top of a narrowband core codec. One challenge in the codec design is the generation of a wideband signal with a very limited additional bit rate (less than 2 kb/s). In this paper, we describe the respective codec layer, which extends the transmitted acoustic bandwidth from the narrowband frequency range (50 Hz-4 kHz) to the wideband frequency range (50 Hz-7 kHz). The underlying algorithm uses a fairly coarse parametric description of the temporal and spectral energy envelopes of the high frequency band (4-7 kHz). This parameter set is quantized with a bit rate of 1.65 kb/s. At the decoder side, the high-frequency components are regenerated by appropriately shaping a synthetically generated ldquoexcitation signal.rdquo Apart from the algorithmic description and a discussion, we state a complexity evaluation as well as some listening test results.