# Cascade Speech Translation for the Kazakh Language
## 2 Related Work
By examining the performance of both cascade and direct approaches in this unique language pair, the study contributed to a more comprehensive understanding of speech translation methodologies and their effectiveness in handling diverse linguistic characteristics. Several prominent speech translation campaigns have made significant contributions to the field. The International Workshop on Spoken Language Translation (IWSLT) is an annual event that serves as a platform for researchers to present their work, participate in shared tasks and engage in evaluations specifically related to spoken language translation [24]. The Workshop on Machine Translation (WMT), although primarily focused on machine translation, also includes a speech translation track where researchers can demonstrate their speech translation systems and take part in evaluations and benchmarking [25]. Speech translation datasets play a crucial role in the development and evaluation of speech translation systems. These datasets consist of parallel audio and text data, enabling the training and evaluation of models that can convert spoken language input into translated text output. The size of speech data in these datasets varies depending on the specific dataset. For instance, MuST-C [26] is a remarkable multilingual speech translation corpus specifically designed to support the training of end-to-end systems for speech-to-text translation (SLT) from English into eight different languages. This dataset stands out due to its substantial size and high quality, making it an invaluable resource for advancing research in the field. MuST-C consists of a minimum of 385 h of audio recordings sourced from the English TED talks. The audio recordings are meticulously aligned at the sentence level with their corresponding manual transcriptions and translations for each target language. The Fisher and Callhome Spanish-English speech translation corpora [27] contribute to the advancement of speech translation research by providing researchers with diverse and accurately aligned speech and text data. The Fisher Spanish dataset is a valuable resource for speech translation research, consisting of 819 transcribed conversations primarily between strangers. It offers approximately 160 h of speech data, meticulously aligned at the utterance level with about 1.5 million tokens. This dataset provides a rich collection of linguistic information for analysis and modeling. The Callhome Spanish corpus, on the other hand, comprises 120 transcripts of spontaneous conversations primarily between friends and family members. It offers approximately 20 h of speech data, aligned at the utterance level, with just over 200,000 words (tokens) of transcribed text. Multilingual TEDx Corpus provides a vast collection of multilingual speeches, contributing to a significant amount of speech data [28]. Similarly, the Europarl-ST Corpus offers extensive multilingual recordings of parliamentary speeches [29]. The direct or end-to-end method is another approach in speech translation that differs from the cascade method discussed in this work. Since the focus of this paper is specifically on the cascade method, the direct method falls outside the scope of this study.