aws-lambda-docker-serverless-inference VS amazon-transcribe-output-word-document

Compare aws-lambda-docker-serverless-inference vs amazon-transcribe-output-word-document and see what are their differences.

amazon-transcribe-output-word-document

An Amazon Transcribe demo to produce a Microsoft Word document containing the turn-by-turn transcription of the audio. This will include additional metadata depending upon the options selected, such as caller sentiment, category identification and issue detection (by aws-samples)
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aws-lambda-docker-serverless-inference amazon-transcribe-output-word-document
1 2
92 44
- -
4.0 1.8
14 days ago about 2 years ago
Jupyter Notebook Python
MIT No Attribution -
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aws-lambda-docker-serverless-inference

Posts with mentions or reviews of aws-lambda-docker-serverless-inference. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-27.

amazon-transcribe-output-word-document

Posts with mentions or reviews of amazon-transcribe-output-word-document. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-11-28.
  • Transcript to word docs
    2 projects | /r/aws | 28 Nov 2022
  • AWS - NLP newsletter - 2021. Aug.
    2 projects | dev.to | 27 Aug 2021
    Amazon Transcribe Call Analytics Amazon Transcribe Call Analytics is a new machine learning (ML) powered conversation insights API that enables developers to improve customer experience and agent productivity. This API can analyze call recordings to generate turn-by-turn call transcripts and actionable insights for understanding customer-agent interactions, identifying trending issues, and tracking performance metrics. Launch content: AWS News Blog, What's New Post, Webpage, Documentation, GitHub Demo, LinkedIn.

What are some alternatives?

When comparing aws-lambda-docker-serverless-inference and amazon-transcribe-output-word-document you can also consider the following projects:

amazon-sagemaker-examples - Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

AutoSub - A CLI script to generate subtitle files (SRT/VTT/TXT) for any video using either DeepSpeech or Coqui

ganbert-pytorch - Enhancing the BERT training with Semi-supervised Generative Adversarial Networks in Pytorch/HuggingFace

kalliope - Kalliope is a framework that will help you to create your own personal assistant.

keytotext - Keywords to Sentences

NeMo - A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)

jetson-containers - Machine Learning Containers for NVIDIA Jetson and JetPack-L4T

amazon-transcribe-post-call-analytics

multi-label-sentiment-classifier - How to build a multi-label sentiment classifiers with Tez and PyTorch

SpeechRecognition - Speech recognition module for Python, supporting several engines and APIs, online and offline.

python-machine-learning-book-3rd-edition - The "Python Machine Learning (3rd edition)" book code repository

hugging-face-workshop - A 90-minute hands on workshop about Hugging Face on SageMaker.