Iskanje po katalogu digitalne knjižnice

Opis: A new parsing method based on the semi-Thue system is described. Similar to, but with more efficient implementation than Markov normal algorithms, it can be used for parsing any recursively enumerable language. Despite its computational power, it is meant to be used primarily for parsing programming and domain-specific languages. It enables a straightforward simulation of a number of existing parsing algorithms based on context-free grammars. The list includes both top-down shift-produce methods (such as SLL and LL) and bottom-up shift-reduce methods (such as LALR and LR), as well as mixed top-down-and-bottom-up methods such as LLLR. To justify the use of the new parsing method, the paper provides numerous examples of how a parser can actually be made in practice. It is advised that the main part of the parser is based on some simple well-established approach, e.g., SLL(1), while syntactically more complicated phrases can be parsed by exploiting the full power of the new parser. These phrases may either be extensions to the original language or some embedded domain-specific language. In all such and similar cases, no part of the language is restricted to be context-free. In fact, context-sensitive languages can be handled quite efficiently.
Ključne besede: Turing-complete parsing, context-sensitive, error recovery
Objavljeno v DKUM: 14.02.2024; Ogledov: 325; Prenosov: 23
Celotno besedilo (534,88 KB)
Gradivo ima več datotek! Več...

Opis: The incorporation of grammatical information into speech recognition systems is often used to increase performance in morphologically rich languages. However, this introduces demands for sufficiently large training corpora and proper methods of using the additional information. In this paper, we present a method for building factored language models that use data obtained by morphosyntactic tagging. The models use only relevant factors that help to increase performance and ignore data from other factors, thus also reducing the need for large morphosyntactically tagged training corpora. Which data is relevant is determined at run-time, based on the current text segment being estimated, i.e., the context. We show that using a context-dependent model in a two-pass recognition algorithm, the overall speech recognition accuracy in a Broadcast News application improved by 1.73% relatively, while simpler models using the same data achieved only 0.07% improvement. We also present a more detailed error analysis based on lexical features, comparing first-pass and second-pass results.
Ključne besede: speech recognition, factored language model, dynamic backoff path, word context, inflectional language, morphosyntactic tags
Objavljeno v DKUM: 26.06.2017; Ogledov: 1829; Prenosov: 372
Celotno besedilo (1,17 MB)
Gradivo ima več datotek! Več...

Opis: My thesis focuses on swearwords in the autobiography of Miles Davis. I define them, explain their function and compare swearwords in the original and the translation. My attempt was to argue the appropriateness of the translation and I used the dictionary of Slovene language (SSKJ) and results from the corpora Fidaplus to provide support for my claims. Context and connotation were among the most important criteria, since these often ruled out a literal translation because they are not used in the same manner in Slovene as in English. A deeper analysis was done on three swearwords: motherfucker, nigger and bitch. The first represents the most difficult challenge for the translator, because it is used in several different ways and can take on numerous functions. A translation for the word does not exist; therefore, the translator had to find several other translation solutions. The analysis has shown that the translator tried to keep one translation solution per function of the word, e.g., pizdun when the word was used to refer to people, and pizdarija when the referent was an object or a situation. However, translating motherfucker often demanded a certain degree of creativity from the translator because it was also used to refer to women or even Davis’ own father, as a means for comparison and as an adjective. It is difficult to find consistent solutions in these cases; therefore, the translator had to adapt his translation to individual cases. Nigger itself was not as challenging as the previous word, because črnuh has already been established as a prototypical translation in Slovene. Albeit several possible translations, e.g. mrha, kuzla, prasica, pička, translations for bitch still raised doubts in some cases. Connotations were of key importance in this case, because they had to match the original, where they could either be positive, negative or neutral. Kuzla was inappropriate in some cases, because it is always used with negative connotations in Slovene; however, mrha is used with all three connotation possibilities and therefore seems to be the most appropriate translation. Generally, I found that translating swearwords is difficult because swearing relies strongly on the originating culture, and each culture is marked by different characteristics; these characteristics, in particular, represent a challenge for the translator.
Ključne besede: translation, swearwords, Miles Davis, autobiography, connotation, context
Objavljeno v DKUM: 14.11.2012; Ogledov: 2066; Prenosov: 97
Celotno besedilo (353,40 KB)