Search

Resumption has been the object of lively research (Doron 1982; Sells 1984; McClauskey 1990; 2002; Shlonsky 1992; Cann 1999; Sharvit 1999; Alexopoulou 2006; Guilliot 2006; Malkawi 2009; Rouveret 2011) and various analyses consider it a form of agreement, a last syntactic resort or a special kind of ellipsis. On the theoretical side, I survey the issues that are the background of the research, such as the nature of the pronouns that are involved in resumption. I develop a syntactic analysis of resumptive pronouns in which they are clitics (Cardinaletti and Starke 1999; Dechaine and Wiltschko 2002; Roberts 2010) and they form a complex determiner phrase together with the relative pronoun or interrogative pronoun. I argue that when resumption is obligatory, it follows from requirements in the syntax and only when it is optional it is a phenomenon at the syntax-pragmatics interface. On the empirical side, I contrast and compare the pronominal paradigms of Arabic and Romanian, an Eastern Romance language which strikingly shows a similar pattern of resumption as Arabic: (i) obligatory resumption in relativization, (ii) designated relative pronoun. Though for Romanian nobody has disputed the nature of the clitic pronouns as clitic in the sense that I am adopting (Cardinaletti and Starke 1999), it has not been thoroughly documented either. I then discuss the pragmatics of resumption in contexts in which it is optional, such as D-linked questions in Arabic. The difference between obligatory resumption and optional resumption is not found in the syntax, because this same syntactic derivation is associated with different interpretive effects depending on whether it occurs in obligatory or in optional contexts. I argue that the presence of the pronoun when it is not required by the syntax triggers a change in interpretation: the module pragmatics assigns it a pragmatic feature.

The musical transcription problem seeks a low-order parametric representation of an audio signal where it is assumed that this signal was generated by one or more musical instruments playing simultaneously. Specialized hardware and software systems exist for transcription of specific instruments playing in isolation, but the general multi-instrument transcription problem has not yet been successfully addressed. It has been observed that single instruments playing notes in isolation leads to highly structured time-frequency descriptions. The desire to exploit this structure has driven the heuristics used in current transcription research. Such structure breaks down, however, as more instruments are added to the signal or it becomes corrupted by reverberation or vibrato, for example. This structural breakdown appears responsible for the poor performance of transcription systems designed for the single-instrument case. In this research, we do away with many of the heuristics of transcription systems, replacing them with statistical signal processing and search algorithms that fundamentally rely upon models of musical instrument behavior. We construct these models based upon statistical characterizations of instrument recordings, which stands in contrast to existing approaches that rely upon only intuitive notions of what features comprise a musical note. We provide an open architecture for optimizing sub-components of the framework and for extending the transcription system to other types of musical sources. Finally, we propose several metrics and test cases for evaluating the performance of any transcription system. We show that our transcription algorithm performs well for both single- and multi-instrument cases.