Speech Translation combines automatic speech recognition (ASR), machine translation (MT), and text-to-speech (TTS) to convert spoken language from one language into another. It enables seamless communication between speakers of different languages, often in real-time. This task begins with ASR, which transcribes the spoken input into text. The text is then translated into the target language using MT models. Finally, TTS converts the translated text back into speech if spoken output is required. Speech Translation presents unique challenges, including handling spontaneous speech, regional accents, and background noise. The system must also preserve the original meaning, cultural nuances, and tone of the speaker during translation. Speech translation is widely used in international conferences, live broadcasts, travel applications, and multilingual customer service. It plays a critical role in breaking down language barriers in real-time conversations. Future research aims to enhance the quality of speech translation through end-to- end models that bypass intermediate steps, enabling faster and more accurate translations across a wider range of languages.