3 research outputs found
Assessing a speakerβs voice quality for forensic purposes: Using the example of creaky voice and breathy voice
The research project explores ways to improve the assessment of voice quality (VQ) for forensic voice comparisons. Until today, a speakerβs VQ is mainly assessed perceptually. However, the field has developed rapidly over the last two decades, prompting calls to objectify the analysis process by relying on voice acoustics instead. This poses a challenge as forensic audio recordings are degraded in several aspects.
The first study focuses on creaky voice (CV), which is particularly multifaceted in production and thus also in acoustics. Therefore, perceptually relevant categories must first be defined and tested before acoustic analysis can be conducted. A new CV classification scheme is conceptualised and tested. It is hypothesised that differences in speaker-specific CV spaces will facilitate speaker discrimination.
Using the example of breathy voice (BV), the second and fourth studies analyse the interplay between perception and acoustics. Spontaneous speech samples of BV speakers are compared with those of non-BV speakers under the studio condition and under the mobile phone condition. Under the studio recording condition, three parameters were found to correlate between perception and acoustics, i.e. H1*-H2*, H1*-A1*, CPP. Under the mobile recording condition, however, low frequency harmonics are attenuated and thus not meaningful. Therefore, the spectral tilt parameters of higher frequencies should be analysed instead.
The third study explores the suitability of f0 estimators with respect to recording condition, and VQ. Valid f0 estimation is required to obtain valid spectral slope measurements. The is explored using sustained cardinal vowels of one male and one female speaker in modal, breathy, and creaky VQ under two recording conditions (studio, mobile phone). Results allow for an informed decision which f0 estimator to use.
The research project sheds light on the needs and possibilities to refine VQ analysis for forensic application
ΠΡΠ½ΠΎΠ²ΠΈ ΠΊΠΎΠΌΠΏβΡΡΠ΅ΡΠ½ΠΎΡ ΠΎΠ±ΡΠΎΠ±ΠΊΠΈ ΠΌΡΠ·ΠΈΠΊΠΈ ΡΠ° ΠΌΠΎΠ²ΠΈ : ΠΠΎΠ½ΡΠΏΠ΅ΠΊΡ Π»Π΅ΠΊΡΡΠΉ
ΠΠ°Π½ΠΈΠΉ Π½Π°Π²ΡΠ°Π»ΡΠ½ΠΈΠΉ ΠΏΠΎΡΡΠ±Π½ΠΈΠΊ ΠΌΡΡΡΠΈΡΡ ΠΊΠΎΠ½ΡΠΏΠ΅ΠΊΡ Π»Π΅ΠΊΡΡΠΉ ΡΠ° ΡΠ΅ΠΎΡΠ΅ΡΠΈΡΠ½Ρ Π²ΡΠ΄ΠΎΠΌΠΎΡΡΡ Π· ΠΎΠ±ΡΠΎΠ±ΠΊΠΈ ΠΌΠΎΠ²Π»Π΅Π½Π½ΡΠ²ΠΈΡ
ΡΠ° ΠΌΡΠ·ΠΈΡΠ½ΠΈΡ
ΡΠΈΠ³Π½Π°Π»ΡΠ² ΠΉ Π·Π°Π±Π΅Π·ΠΏΠ΅ΡΡΡ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π½Ρ Π»Π΅ΠΊΡΡΠΉΠ½ΠΈΡ
ΡΠ° ΠΏΡΠ°ΠΊΡΠΈΡΠ½ΠΈΡ
Π·Π°Π½ΡΡΡ ΠΎΡΠ²ΡΡΠ½ΡΠΎΠ³ΠΎ ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΡ Β«ΠΡΠ½ΠΎΠ²ΠΈ ΠΊΠΎΠΌΠΏβΡΡΠ΅ΡΠ½ΠΎΡ ΠΎΠ±ΡΠΎΠ±ΠΊΠΈ ΠΌΡΠ·ΠΈΠΊΠΈ ΡΠ° ΠΌΠΎΠ²ΠΈΒ» Π΄Π»Ρ Π·Π΄ΠΎΠ±ΡΠ²Π°ΡΡΠ² ΠΎΡΠ²ΡΡΠΈ ΡΡΠ²Π½Ρ ΠΏΡΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠΈ Β«Π±Π°ΠΊΠ°Π»Π°Π²ΡΒ».
Π ΠΎΠ·Π³Π»ΡΠ½ΡΡΠΎ ΠΏΠΈΡΠ°Π½Π½Ρ Π»ΡΠ½ΡΠΉΠ½ΠΎΡ ΡΠ° Π½Π΅Π»ΡΠ½ΡΠΉΠ½ΠΎΡ ΡΠΈΡΡΠΎΠ²ΠΎΡ ΠΎΠ±ΡΠΎΠ±ΠΊΠΈ Π°ΠΊΡΡΡΠΈΡΠ½ΠΈΡ
ΡΠΈΠ³Π½Π°Π»ΡΠ², ΡΡΠ²ΠΎΡΠ΅Π½Π½Ρ Π°ΡΠ΄ΡΠΎΠ΅ΡΠ΅ΠΊΡΡΠ², Π΄ΡΠ°Π³Π½ΠΎΡΡΠΈΠΊΠΈ Π²ΠΎΠΊΠ°Π»ΡΠ½ΠΎΠ³ΠΎ Π°ΠΏΠ°ΡΠ°ΡΡ Π»ΡΠ΄ΠΈΠ½ΠΈ ΡΠ° ΠΌΡΠ·ΠΈΡΠ½ΠΈΡ
ΡΠ½ΡΡΡΡΠΌΠ΅Π½ΡΡΠ², ΠΌΠ°ΡΠΊΡΠ²Π°Π½Π½Ρ ΠΌΠΎΠ²Π»Π΅Π½Π½Ρ, ΠΊΠΎΠ΄ΡΠ²Π°Π½Π½Ρ ΠΌΠΎΠ²Π»Π΅Π½Π½ΡΠ²ΠΈΡ
ΡΠΈΠ³Π½Π°Π»ΡΠ². Π’Π΅ΠΎΡΠ΅ΡΠΈΡΠ½ΠΈΠΉ ΠΌΠ°ΡΠ΅ΡΡΠ°Π» ΡΠ΅ΡΠ³ΡΡΡΡΡΡ ΡΠ· ΠΏΡΠ°ΠΊΡΠΈΡΠ½ΠΈΠΌΠΈ Π²ΠΏΡΠ°Π²Π°ΠΌΠΈ, ΡΠΏΡΡΠΌΠΎΠ²Π°Π½ΠΈΠΌΠΈ Π½Π° Π·Π°ΡΠ²ΠΎΡΠ½Π½Ρ ΠΌΠ΅ΡΠΎΠ΄ΡΠ² ΠΊΠΎΠΌΠΏβΡΡΠ΅ΡΠ½ΠΎΠ³ΠΎ ΠΌΠΎΠ΄Π΅Π»ΡΠ²Π°Π½Π½Ρ ΡΠ° ΡΠΎΠ·Π²βΡΠ·Π°Π½Π½Ρ ΡΠ½ΠΆΠ΅Π½Π΅ΡΠ½ΠΎ-ΡΠ΅Ρ
Π½ΡΡΠ½ΠΈΡ
Π·Π°Π΄Π°Ρ Π² ΡΠ΅ΡΠ΅Π΄ΠΎΠ²ΠΈΡΡ Matlab. Π’Π΅ΠΊΡΡΠΈ ΠΊΠΎΠΌΠΏβΡΡΠ΅ΡΠ½ΠΈΡ
ΠΏΡΠΎΠ³ΡΠ°ΠΌ ΡΠ° Π·ΡΠ°Π·ΠΊΠΈ ΠΌΡΠ·ΠΈΡΠ½ΠΈΡ
ΡΠ° ΠΌΠΎΠ²Π»Π΅Π½Π½ΡΠ²ΠΈΡ
ΡΠΈΠ³Π½Π°Π»ΡΠ² ΡΠΎΠ·ΠΌΡΡΠ΅Π½ΠΎ Π² Π¦Π΅Π½ΡΡΡ ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΠΉΠ½ΠΈΡ
ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΡΠΉ Π² ΠΎΡΠ²ΡΡΡ ΠΠΠ ΡΠΌ. ΠΠ³ΠΎΡΡ Π‘ΡΠΊΠΎΡΡΡΠΊΠΎΠ³ΠΎ, Π° ΡΠ°ΠΊΠΎΠΆ Π² ΠΡΠ³Π»-ΠΊΠ»Π°ΡΡ ΠΎΡΠ²ΡΡΠ½ΡΠΎΠ³ΠΎ ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΡ Β«ΠΡΠ½ΠΎΠ²ΠΈ ΠΊΠΎΠΌΠΏβΡΡΠ΅ΡΠ½ΠΎΡ ΠΎΠ±ΡΠΎΠ±ΠΊΠΈ ΠΌΡΠ·ΠΈΠΊΠΈ ΡΠ° ΠΌΠΎΠ²ΠΈΒ».
ΠΠ°Π²ΡΠ°Π»ΡΠ½ΠΈΠΉ ΠΏΠΎΡΡΠ±Π½ΠΈΠΊ Π±ΡΠ΄Π΅ ΡΠ°ΠΊΠΎΠΆ ΠΊΠΎΡΠΈΡΠ½ΠΈΠΌ ΡΡΡΠ΄Π΅Π½ΡΠ°ΠΌ Π°ΠΊΡΡΡΠΈΡΠ½ΠΈΡ
ΡΠ° ΡΠ΅Π»Π΅ΠΊΠΎΠΌΡΠ½ΡΠΊΠ°ΡΡΠΉΠ½ΠΈΡ
ΡΠΏΠ΅ΡΡΠ°Π»ΡΠ½ΠΎΡΡΠ΅ΠΉ ΡΠ΅Ρ
Π½ΡΡΠ½ΠΈΡ
Π½Π°Π²ΡΠ°Π»ΡΠ½ΠΈΡ
Π·Π°ΠΊΠ»Π°Π΄ΡΠ², ΡΠΎ Π½Π°Π²ΡΠ°ΡΡΡΡΡ Π·Π° ΡΠΏΠ΅ΡΡΠ°Π»ΡΠ½ΡΡΡΡ Β«ΠΠ»Π΅ΠΊΡΡΠΎΠ½ΡΠΊΠ°Β», Π° ΡΠ°ΠΊΠΎΠΆ ΡΠ°Ρ
ΡΠ²ΡΡΠΌ Π² Π³Π°Π»ΡΠ·Ρ Π°ΠΊΡΡΡΠΈΡΠ½ΠΎΡ Π΅ΠΊΡΠΏΠ΅ΡΡΠΈΠ·ΠΈ ΡΠ° ΠΊΠΎΡΠ΅ΠΊΡΡΡ ΠΊΠΎΠΌΡΠ½ΡΠΊΠ°ΡΡΠΉΠ½ΠΈΡ
ΠΊΠ°Π½Π°Π»ΡΠ².This study guide contains a synopsis of lectures and theoretical information on speech and music signal processing and provides lectures and practical sessions of the educational component "Fundamentals of Computer Music and Speech Processing" for students of the "Bachelor" level of education.
The issues of linear and nonlinear digital processing of acoustic signals, creation of audio effects, diagnostics of the human vocal apparatus and musical instruments, masking of speech, coding of speech signals are considered. Theoretical material alternates with practical exercises aimed at mastering computer modeling methods and solving engineering and technical problems in the Matlab environment. Texts of computer programs and samples of music and speech signals are located in the Center for Information Technologies in Education of KPI named after Igor Sikorsky, as well as in the Google class of the educational component "Fundamentals of computer processing of music and speech".
The study guide will also be useful for students of acoustic and telecommunication specialties of technical educational institutions, studying in the specialty "Electronics", as well as specialists in the field of acoustic examination and correction of communication channels