Philipp Aichinger

Inter-device reliability of DSI measurement

Abstract The Dysphonia Severity Index (DSI) is a measure that quantifies the overall vocal quality. The aim of the study is to evaluate the reliability of DSI measurements. The DSIs of 30 subjects were therefore measured using LingWAVES (WEVOSYS) and DiVAS (XION). To evaluate the inter-device reliability of DSI measurement, the devices’ results were compared for each subject. The DSI values of both devices showed great differences. The calculated DSI differences of 95% of the subjects were within the limits of +2.39 and –2.82, which makes a clinical interpretation of severity of voice disorder using different devices questionable. The technical and procedural aspects of measurement divergences are discussed, and the need to define hardware and software standards is shown.

Towards Objective Voice Assessment: The Diplophonia Diagram.

OBJECTIVES Diplophonia is an often misinterpreted symptom of disordered voice, and needs objectification. An audio signal processing algorithm for the detection of diplophonia is proposed. Diplophonia is produced by two distinct oscillators, which yield a profound physiological interpretation. The algorithms performance is compared with the clinical standard parameter degree of subharmonics (DSH). STUDY DESIGN This is a prospective study. METHODS A total of 50 dysphonic subjects with (28 with diplophonia and 22 without diplophonia) and 30 subjects with euphonia were included in the study. From each subject, up to five sustained phonations were recorded during rigid telescopic high-speed video laryngoscopy. A total of 185 phonations were split up into 285 analysis segments of homogeneous voice qualities. In accordance to the clinical group allocation, the considered segmental voice qualities were (1) diplophonic, (2) dysphonic without diplophonia, and (3) euphonic. The Diplophonia Diagram is a scatter plot that relates the one-oscillator synthesis quality (SQ1) to the two-oscillator synthesis quality (SQ2). Multinomial logistic regression is used to distinguish between diplophonic and nondiplophonic segments. RESULTS Diplophonic segments can be well distinguished from nondiplophonic segments in the Diplophonia Diagram because two-oscillator synthesis is more appropriate for imitating diplophonic signals than one-oscillator synthesis. The detection of diplophonia using the Diplophonia Diagram clearly outperforms the DSH by means of positive likelihood ratios (56.8 versus 3.6). CONCLUSIONS The diagnostic accuracy of the newly proposed method for detecting diplophonia is superior to the DSH approach, which should be taken into account for future clinical and scientific work.

Double pitch marks in diplophonic voice

Determination of pitch marks (PMs) is necessary in clinical voice assessment for the measurement of fundamental frequency (F0) and perturbation. In voice with ambiguous F0, PM determination is crucial, and its validity needs special attention. The study at hand proposes a new approach for PM determination from Laryngeal High-Speed Videos (LHSVs), rather than from the audio signal. In this novel approach, double PMs are extracted from a diplophonic voice sample, in order to account for ambiguous F0s. The LHSVs are spectrally analyzed in order to extract dominant oscillation frequencies of the vocal folds. Unit pulse trains with these frequencies are created as PM trains and compensated for the phase shift. The PMs are compared to Praats single audio PMs. It is shown that double PMs are needed in order to analyze diplophonic voice, because traditional single PMs do not explain its double-source characteristic.

Diplophonia Disturbs Jitter and Shimmer Measurement

Objectives: The aims of this study are to investigate the effects of diplophonia on jitter and shimmer and to identify measurement limitations with regard to material selection and clinical interpretation. Materials and Methods: Four hundred and ninety-eight audio samples of sustained phonations were analyzed. The audio samples were assessed for the grade of hoarseness and the presence of diplophonia. Jitter and shimmer were reported with regard to perceptual ratings. We investigated cycle marker positions exemplarily and qualitatively to understand their implications for perturbation measurements. Results: Medians of jitter and shimmer were higher for diplophonic voices than for nondiplophonic voices with equal grades of hoarseness. The variance of jitter for moderately dysphonic voices was larger than the variance observed in a corpus from which diplophonic samples had been discarded. The positions of cycle markers in diplophonic voices did not match the positions of the pulses, indicating that the validity of jitter and shimmer values for these voices were questionable. Conclusion: Diplophonia biases the reporting of dysphonia severity via perturbation measures, and their validity is questionable for these voices. In addition, diplophonia is an influential source of variance in jitter measurements. Thus, diplophonic fragments of voice samples should be excluded prior to perturbation analysis.

Fundamental frequency tracking in diplophonic voices

Abstract Background and objectives Fundamental frequency ( f o ) extraction in disordered voices is a prerequisite for many types of clinical analyses. Special attention must be paid if multiple oscillators with different f o s are active simultaneously. Two independent approaches to f o tracking in diplophonic voices are proposed and compared with a benchmark from the literature. Material and methods Six samples of sustained phonations were analyzed. High-speed videos were obtained in addition to audio recordings. Video-based f o tracks were obtained from cycle marks that report maximal vocal fold deflection in digital kymograms. Audio waveform modeling based extraction involved candidate tracking, oscillator waveform synthesis and track selection. Audio subband auto-correlation based extraction served as a benchmark. Results and discussion Promising qualitative and quantitative agreement of audio waveform modeling based estimates with kymogram-based tracks was observed. With reference to the kymogram-based tracks, audio waveform modeling based extraction had a median total error rate of 1.9%, which is an improvement over the benchmark method (17.7%). Conclusion The results illustrate that f o s of diplophonic voices may be validly obtained from kymogram cycle marks, as well as via audio waveform modeling. The acquisition of two simultaneous f o tracks in diplophonic voices may increase the validity of clinical voice analysis procedures in the future.

Comparison of an audio-based and a video-based approach for detecting diplophonia

Abstract Background and objectives Diplophonia is a common symptom in voice disorders. Depending on the underlying aetiology, diplophonic patients typically need treatment such as phonosurgery or speech therapy. In current clinical practice, the presence of diplophonia is assessed by auditive rating. To avoid subjectivity in voice assessment and to follow principles of evidence based medicine, objective instrumental assessment methods are needed. In order to gain insight into instrumental assessment of diplophonic voice, comparisons between different assessment approaches are necessary. The aim of the study is to compare the performance of two independent objective approaches on their ability to detect diplophonia. The compared approaches are the formerly published degree of subharmonics (DSH), and a newly proposed measure for spatial bimodality of the vocal fold vibration. Material and methods From a clinical database of 352 laryngeal high-speed videos with synchronous audio recordings, 60 phonation segments (20 euphonic, twenty diplophonic and twenty non-diplophonic dysphonic) were auditively selected. For all phonation segments, the DSH and the newly proposed measure for spatial bimodality were determined. The DSH is the occurrence rate of audio analysis blocks with ambiguous fundamental frequency in percent. The bimodality measure quantifies the spatial occurrence of secondary oscillation frequencies along the vocal folds’ edges. Both the DSH and the bimodality measure are evaluated on their ability to detect diplophonia by means of cut off threshold classification. Results and conclusions The DSH showed excellent classification rates for separating diplophonic from euphonic phonation (sensitivity: 98.4%, specificity: 100%). In separating diplophonic from non-diplophonic dysphonic phonation, the bimodality measure slightly outperforms the DSH approach (sensitivity: 54.6%, specificity: 92.7%). The separation of diplophonia from other kinds of dysphonia is challenging, and more sophisticated methods are needed. It is concluded that auditive and glottal diplophonia must be distinguished. As the clinical assessment of diplophonia primarily aims at determining glottal conditions, the video-based approach might deliver clinically more relevant data than the auditive approach.