Influence of recovery intensity on oxygen demand and repeated sprint performance

AIM: This study aimed to determine effects of recovery intensity (passive, 20, 30 and 40%V̇ O2peak) on oxygen uptake kinetics, performance and blood lactate accumulation during repeated sprints. METHODS: 7 moderately-trained male participants (V̇O2peak: 48.1 ± 5.1 ml·kg-1·min-1) performed 4 x 30-s repeated Wingate tests on 4 separate occasions. RESULTS: Recovery of V̇ O2 between sprints was prolonged with recovery intensity (time required to reach 50% V̇O2peak: Passive: 50 ± 9; 20%: 81 ± 17; 30%: 130 ± 43; 40%: 188 ± 62 sec, P<0.001), while V̇O2-to-sprint work ratio was mainly increased by the higher intensities (Passive: 138 ± 17; 20%: 149 ± 14; 30%: 159 ± 15; 40%: 158 ± 17 ml·min-1·kJ-1, P=0.001). The decline in peak power tended to be greater in the higher intensity conditions during sprint 2 (Passive: 7.4 ± 5.4; 20%: 5.8 ± 7.9; 30%: 12.7 ± 7.4; 40%: 12.7 ± 5.5%, P=0.052), whereas average power was less decreased with recovery intensity during sprint 4 (Passive: 22.4 ± 8.9; 20%: 19.9 ± 6.1; 30%: 18.4 ± 7.3; 40%: 16.6 ± 6.2%, P=0.036). Blood lactate was not different with recovery intensity (P=0.251). CONCLUSION: The present study demonstrated that while the higher recovery intensities induce prolonged oxygen recovery and impaired peak power restoration during the initial sprints, those intensities provide a greater aerobic contribution to sprint performance, resulting in better power maintenance during the latter sprints

Effects of reduced-volume of sprint interval training and the time course of physiological and performance adaptations

This study sought to determine the time course of training adaptations to two different sprint interval training programmes with the same sprint: rest ratio (1:8) but different sprint duration. Nine participants (M: 7; F: 2) were assigned to 15-s training group (15TG) consisting of 4 to 6 x 15-s sprints interspersed with 2-min recovery, whereas eight participants (M: 5; F: 3) were assigned to 30-s training group (30TG) consisting of 4 to 6 30-s sprints interspersed with 4-min recovery. Both groups performed their respective training twice per week over 9 weeks and changes in peak oxygen uptake (V̇O2peak) and time to exhaustion (TTE) were assessed every 3 weeks. Additional 8 healthy active adults (M: 6; F: 2) completed the performance assessments 9 weeks apart without performing training (control group, CON). Following 9 weeks of training, both groups improved V̇O2peak (15TG: 12.1%; 30TG: 12.8%, P < 0.05) and TTE (15TG: 16.2%; 30TG: 12.8%, P < 0.01) to a similar extent. However, while both groups showed the greatest gains in V̇O2peak at 3 weeks (15TG: 16.6%; 30TG: 17.0%, P < 0.001), those in TTE were greatest at 9 weeks. CON did not change any of performance variables following 9 weeks. This study demonstrated that whilst the changes in cardiorespiratory function plateau within several weeks with sprint interval training, endurance capacity (TTE) is more sensitive to such training over a longer time frame in moderately-trained individuals. Furthermore, a 50% reduction in sprint duration does not diminish overall training adaptations over 9 weeks

Combining vocal tract length normalization with hierarchial linear transformations

Recent research has demonstrated the effectiveness of vocal tract length normalization (VTLN) as a rapid adaptation technique for statistical parametric speech synthesis. VTLN produces speech with naturalness preferable to that of MLLR-based adaptation techniques, being much closer in quality to that generated by the original av-erage voice model. However with only a single parameter, VTLN captures very few speaker specific characteristics when compared to linear transform based adaptation techniques. This paper pro-poses that the merits of VTLN can be combined with those of linear transform based adaptation in a hierarchial Bayesian frame-work, where VTLN is used as the prior information. A novel tech-nique for propagating the gender information from the VTLN prior through constrained structural maximum a posteriori linear regres-sion (CSMAPLR) adaptation is presented. Experiments show that the resulting transformation has improved speech quality with better naturalness, intelligibility and improved speaker similarity. Index Terms — Statistical parametric speech synthesis, hidden Markov models, speaker adaptation, vocal tract length normaliza-tion, constrained structural maximum a posteriori linear regression 1

HMM-based speech synthesiser using the LF-model of the glottal source

A major factor which causes a deterioration in speech quality in HMM-based speech synthesis is the use of a simple delta pulse signal to generate the excitation of voiced speech. This paper sets out a new approach to using an acoustic glottal source model in HMM-based synthesisers instead of the traditional pulse signal. The goal is to improve speech quality and to better model and transform voice characteristics. We have found the new method decreases buzziness and also improves prosodic modelling. A perceptual evaluation has supported this finding by showing a 55.6 % preference for the new system, as against the baseline. This improvement, while not being as significant as we had initially expected, does encourage us to work on developing the proposed speech synthesiser further

Cepstral analysis based on the Glimpse proportion measure for improving the intelligibility of HMM-based synthetic speech in noise

In this paper we introduce a new cepstral coefficient extraction method based on an intelligibility measure for speech in noise, the Glimpse Proportion measure. This new method aims to increase the intelligibility of speech in noise by modifying the clean speech, and has applications in scenarios such as public announcement and car navigation systems. We first explain how the Glimpse Proportion measure operates and further show how we approximated it to integrate it into an existing spectral envelope parameter extraction method commonly used in the HMM-based speech synthesis framework. We then demonstrate how this new method changes the modelled spectrum according to the characteristics of the noise and show results for a listening test with vocoded and HMM-based synthetic speech. The test indicates that the proposed method can significantly improve intelligibility of synthetic speech in speech shaped noise. Index Terms — cepstral coefficient extraction, objective measure for speech intelligibility, Lombard speech, HMM-based speech synthesis 1