[Question]: About realtime translation and presentation

[dinhan92]

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• [X] I have searched both the documentation and discord for an answer.

Question

Is there a way that I can use this package for realtime translation with live subtitle when presentation with powerpoint? I mean in powerpoint, using live subtitle, the spoken language does not have my country language. I hope that I can use llama index for that.

Need some help! Pls!

[dosubot[bot]]

LlamaIndex does not have specific examples or documentation for integrating with PowerPoint or similar presentation software for real-time translation and live subtitles. However, LlamaIndex does support real-time data processing and streaming capabilities, which could be leveraged for such a use case.

To achieve real-time translation with live subtitles, you can use LlamaIndex's built-in support for handling audio input and converting it to text. Here are the steps you can follow:

1. Transcribe Audio to Text: Use LlamaIndex's integration with audio transcription tools like Azure Speech, AssemblyAI, or OpenAI's Whisper model to transcribe the spoken language into text.

   Example using Azure Speech Tool:

   from llama_index.tools.azure_speech import AzureSpeechToolSpec
   from llama_index.agent.openai import OpenAIAgent
   
   speech_tool = AzureSpeechToolSpec(speech_key="your-key", region="eastus")
   
   agent = OpenAIAgent.from_tools(
      speech_tool.to_tool_list(),
      verbose=True,
   )
   print(agent.chat("summarize the data/speech.wav audio file into a few sentences"))

   Example using AssemblyAI:

   from llama_index.readers.assemblyai import AssemblyAIAudioTranscriptReader
   
   audio_file = "https://storage.googleapis.com/aai-docs-samples/nbc.mp3"
   reader = AssemblyAIAudioTranscriptReader(file_path=audio_file)
   
   docs = reader.load_data()
   print(docs[0].text)

   Example using OpenAI Whisper:

   from pathlib import Path
   from llama_index.readers.file.video_audio.base import VideoAudioReader
   
   reader = VideoAudioReader(model_version="base")
   transcripts = reader.load_data(Path("path/to/your/audio/file.mp3"))
   for document in transcripts:
      print(document.text)

2. Translate Text: Configure LlamaIndex to use a custom language model for translation purposes. You can define a custom LLM and update prompts to enforce the output language.

   Example:

   from llama_index.core import Settings
   from llama_index.llms.openai import OpenAI
   
   llm = OpenAI(system_prompt="Always respond in your desired language.")
   
   # set a global llm
   Settings.llm = llm
   
   query_engine = load_index_from_storage(
      storage_context,
   ).as_query_engine()

3. Display Subtitles: Integrate the transcribed and translated text with PowerPoint's live subtitle feature. This step may require custom development to feed the translated text into PowerPoint's subtitle system in real-time.

By combining these steps, you can create a workflow that transcribes spoken language, translates it, and displays it as live subtitles in PowerPoint.

For more details on audio transcription and custom LLM configuration, refer to the following sources:

• Azure Speech Tool ^[1]
• AssemblyAI ^[2]
• OpenAI Whisper ^[3]
• Custom LLM configuration ^[4]

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