Intelligibility evaluation of Ramsey-derived interleavers for internet voice streaming with the iLBC codec

This paper focuses on the application of a previously proposed interleaving, derived from the Ramsey convolutional class, in a voice streaming context with bursty packet losses. This kind of interleaving has already shown significant improvements in a distributed speech recognition context, in comparison with the widely used minimum latency block interleavers (MLBI). Here, the effectiveness of these interleavers is evaluated with an internet-oriented speech codec, such as iLBC. Since iLBC avoids error propagation due to lost frames and only uses the previously received frame to recover from those, Ramsey interleaving turns out especially suitable for this codec. In order to measure the performance of the system, the ITU PESQ algorithm is applied along with an intelligibility criterion based on the accuracy obtained through an automatic speech recognizer (ASR). In addition, an informal subjective test is carried out to corroborate the ASR scores. Results show that the proposed Ramsey-derived interleaving provides at least the same quality and better intelligibility than the MLBI ones when it is applied to iLBC codec.