Communication during induction of paediatric anaesthesia: an observational study.

We aimed to identify and categorise advanced communication skills used by experienced consultant paediatric anaesthetists to facilitate the induction of paediatric anaesthesia. The communication techniques were both verbal and non-verbal. Communications with potentially negative effects were also noted. Eighty-three inductions were observed over a three-month period. The 12 anaesthetists observed were all senior consultants at a tertiary referral paediatric centre. The mean age of patients was 6.1 years SD+/-4.8. There were 53 males (63.9%) and 30 females (36.1%). A first anaesthetic was administered to 43 patients (56%) and sedative premedication to six (8%). Inhalational inductions were observed in 59 patients (71%). The remainder received an intravenous induction. Anaesthesia was induced in the operating room on 68 occasions (82%), in the induction room on 11 (13%) and in the radiology department on 4(5%). The most common communication techniques used were: voice change in 60 (72%); distraction in 49 (59%); direct commands in 39 (47%); repetition in 34 (41%); imagery in 21 (25%) and focused attention 21 (25%). Other techniques used were seeding of ideas, utilisation, non-verbal cues, double-binds, story-telling, indirect suggestion, dissociation and reversed effect. Sabotage by parents or staff such as inadvertent negative suggestions, was observed on 14 occasions (17%). Paediatric anaesthetists utilise a wide range of communication techniques in a highly flexible manner when inducing anaesthesia in children. Many of these communications can be characterised as hypnotherapeutic. Our observations suggest that formal structured training in communication skills and further research is warranted.

Noisy speech recognition using de-noised multiresolution analysis acoustic features.

This paper describes a novel application of multiresolution analysis (MRA) in extracting acoustic features that possess de-noising capability for robust speech recognition. The MRA algorithm is used to construct a mel-scaled wavelet packet filter-bank, from which subband powers are computed as the feature parameters for speech recognition. Wiener filtering is applied to a few selected subbands at some intermediate stages of decomposition. For high-frequency bands, Wiener filters are designed based on a reduced fraction of the estimated noise power, making the consonant features much more prominent and contrastive. The proposed method is evaluated in phone recognition experiments with the TIMIT database. In the presence of stationary white noise at 10-dB SNR, the de-noised MRA features attain a phone recognition rate of 32%. There is a noticeable improvement compared with the accuracy of 29% and 20% attained by the commonly used mel-frequency cepstral coefficients (MFCC) with and without cepstral mean normalization (CMN), respectively. The effectiveness of the MRA features is also verified by the fact that they exhibit smaller distortion from clean speech.

Quad-band excitation for low bit rate speech coding.

The excitation parameters of a multiband excitation model for speech production consist of a pitch period and a series of voiced/unvoiced (v/uv) decisions for a number of fixed frequency bands around the harmonics of the fundamental. In this paper, it is shown that, at most, four v/uv variable-length nonoverlapping frequency bands spanning over the telephone bandwidth are adequate to represent the excitation spectrum that provides an improved modeling of mixed voicing and noisy speech. A quad-band excitation (QBE) method is presented which generates excitation source for a linear prediction vocoder for low bit rate transmission of speech signal and the DRT scores validate the potential of the method.