The efficacy of aural modeling in music education at the primary and secondary levels is well documented, and anecdotal evidence among university studio voice teachers abounds. However, this topic has not previously been explored with undergraduate level singers using acoustic analysis of the singing voice. This investigation utilized a survey on listening behaviors to examine undergraduate voice students’ use of recorded aural models. In addition, an empirical study measured the effect of repeated exposure to recorded aural models on participants’ vocal production. Research was conducted at Southwestern University, a private liberal arts institution in Georgetown, Texas. Study participants were divided into two groups. The control group performed a newly-composed melody after a recorded aural model of the melody was played a single time. The experimental group completed 10-minute listening assignments once a day for a five-day period before performing the same melody. Data between the non-listening and listening groups was compared. Using a second newly composed melody, the control group then completed a five-day listening assignment and performed the second melody. Pre- and post-listening data from this group of subjects was compared. Listening assignments were adapted from a speech pathology remediation technique known as auditory bombardment. They involved listening to multiple repetitions of the recorded aural model without attempting to practice singing the melody. The study measured four acoustic parameters: musical accuracy (pitch and rhythm), vowel/consonant articulation, use of vibrato, and ratio of power between overtones above and below 2 kHz. The listening behavior survey revealed that most students use recorded aural models in their practice time. However, results indicated that students would benefit from professional quality aural models and specific information about appropriate time parameters for listening activities. Results of the empirical study revealed a statistically significant 20-30% improvement in vocal production in both the experimental listening group and the control group post-listening. These data demonstrate that focused periods of listening to an aural model are effective in improving vocal production, even within a short period of time. The results of this study support the inclusion of aural modeling in the applied voice studio. / text

This dissertation is concerned with the problem of describing the singing voice within the audio signal of a song. This work is motivated by the fact that the lead vocal is the element that attracts the attention of most listeners. For this reason it is common for music listeners to organize and browse music collections using information related to the singing voice such as the singer name. Our research concentrates on the three major problems of music information retrieval: the localization of the source to be described (i.e. the recognition of the elements corresponding to the singing voice in the signal of a mixture of instruments), the search of pertinent features to describe the singing voice, and finally the development of pattern recognition methods based on these features to identify the singer. For this purpose we propose a set of novel features computed on the temporal variations of the fundamental frequency of the sung melody. These features, which aim to describe the vibrato and the portamento, are obtained with the aid of a dedicated model. In practice, these features are computed on the time-varying frequency of partials obtained using the sinusoidal model. In the first experiment we show that partials corresponding to the singing voice can be accurately differentiated from the partials produced by other instruments using decisions based on the parameters of the vibrato and the portamento. Once the partials emitted by the singer are identified, the segments of the song containing singing can be directly localized. To improve the recognition of the partials emitted by the singer we propose to group partials that are related harmonically. Partials are clustered according to their degree of similarity. This similarity is computed using a set of CASA cues including their temporal frequency variations (i.e. the vibrato and the portamento). The clusters of harmonically related partials corresponding to the singing voice are identified using the vocal vibrato and the portamento parameters. Groups of vocal partials can then be re-synthesized to isolate the voice. The result of the partial grouping can also be used to transcribe the sung melody. We then propose to go further with these features and study if the vibrato and portamento characteristics can be considered as a part of the singers' signature. Previous works on singer identification describe audio signals using features extracted on the short-term amplitude spectrum. The latter features aim to characterize the timbre of the sound, which, in the case of singing, is related to the vocal tract of the singer. The features we develop in this document capture long-term information related to the intonation of the singer, which is relevant to the style and the technique of the singer. We propose a method to combine these two complementary descriptions of the singing voice to increase the recognition rate of singer identification. In addition we evaluate the robustness of each type of feature against a set of variations. We show the singing voice is a highly variable instrument. To obtain a representative model of a singer's voice it is thus necessary to build models using a large set of examples covering the full tessitura of a singer. In addition, we show that features extracted directly from the partials are more robust to the presence of an instrumental accompaniment than features derived from the amplitude spectrum.

Dans ce mémoire, nous avons étudié l’impact du mouvement HIP (Historically informed performance) sur la manière dont les flûtistes interprètent le répertoire baroque depuis 60 ans. Nous avons analysé avec Sonic visualiser des enregistrements de cinq flûtistes, réalisés tant sur la flûte baroque que la flûte moderne. Le logiciel a permis de générer des données graphiques qui appuient objectivement les constats observés en ce qui a trait au tempo, aux ornements, aux articulations, aux nuances et au vibrato. En comparant ces enregistrements, nous avons remarqué qu’il existe plusieurs points communs entre les interprètes qui jouent sur un instrument baroque et ceux qui jouent sur un instrument moderne, au point où l’on peut parler d’un transfert des pratiques d’interprétation de l’un vers l’autre. Nous avons aussi fait une synthèse de quelques sources baroques afin de vérifier dans quelle mesure les interprètes observent ces indications. Nous avons observé qu’au cours des années, le mouvement HIP a changé la définition de ce qu’est une interprétation authentique et qu’il a modifié la manière dont les flûtistes modernes dans leur ensemble interprètent la musique baroque. / In this master’s thesis, we studied how the historically informed performance (HIP) movement has impacted the way flutists have approached Baroque repertoire since 1960. We analyzed recordings from five flute players with Sonic Visualiser. We used this software to generate graphical data to objectively support our observations on tempo, articulation, dynamics, and vibrato. By comparing recordings made on baroque and modern instruments, we found that in the past 20 years, flutists who are performing this repertoire on the modern flute started integrating performance practice from the baroque players in their own performance of early music. To contextualize the performance practices, we synthesized a few baroque sources to verify the extent to which flutists have respected these indications. Through the process of this research, we observed that the HIP movement has changed the definition of an authentic performance of early music and that it has modified the way modern flutists perform Baroque music.

This diploma thesis deals with design and implementation of complex software system for post-production of popular music. The system was implemented as a plug-in module in C++ language using JUCE application framework. The emphasis was on creating a well arranged and intuitive graphic user interface. The plug-in provides a set of audio effects and processors that can be connected into the desired graph structure. For less experienced users, there is a database of preset configurations usable for a variety of input signals.

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In mathematical finance, the sensitivities of option prices to various market parameters, also known as the “Greeks”, reflect the exposure to different sources of risk. Computing these is essential to predict the impact of market moves on portfolios and to hedge them adequately. This is commonly done using Monte Carlo simulations. However, obtaining accurate estimates of the Greeks can be computationally costly. Multilevel Monte Carlo offers complexity improvements over standard Monte Carlo techniques. However the idea has never been used for the computation of Greeks. In this work we answer the following questions: can multilevel Monte Carlo be useful in this setting? If so, how can we construct efficient estimators? Finally, what computational savings can we expect from these new estimators? We develop multilevel Monte Carlo estimators for the Greeks of a range of options: European options with Lipschitz payoffs (e.g. call options), European options with discontinuous payoffs (e.g. digital options), Asian options, barrier options and lookback options. Special care is taken to construct efficient estimators for non-smooth and exotic payoffs. We obtain numerical results that demonstrate the computational benefits of our algorithms. We discuss the issues of convergence of pathwise sensitivities estimators. We show rigorously that the differentiation of common discretisation schemes for Ito processes does result in satisfactory estimators of the the exact solutions’ sensitivities. We also prove that pathwise sensitivities estimators can be used under some regularity conditions to compute the Greeks of options whose underlying asset’s price is modelled as an Ito process. We present several important results on the moments of the solutions of stochastic differential equations and their discretisations as well as the principles of the so-called “extreme path analysis”. We use these to develop a rigorous analysis of the complexity of the multilevel Monte Carlo Greeks estimators constructed earlier. The resulting complexity bounds appear to be sharp and prove that our multilevel algorithms are more efficient than those derived from standard Monte Carlo.