STT
Apache Spark
STT | Apache Spark | |
---|---|---|
11 | 101 | |
2,144 | 38,378 | |
1.9% | 0.6% | |
0.6 | 10.0 | |
about 2 months ago | 7 days ago | |
C++ | Scala | |
Mozilla Public License 2.0 | Apache License 2.0 |
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STT
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Rest in Peas: The Unrecognized Death of Speech Recognition (2010)
What has happened since then? I know Common Voice has come and gone https://en.wikipedia.org/wiki/Common_Voice https://github.com/coqui-ai/STT
And I've seen some neural approaches too
No idea where to look for comparisons though.
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Numen - FOSS voice control for handsfree computing
I basically just used coqui stt https://github.com/coqui-ai/STT
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Are there any OCR and Speech-to-Text services that are privacy friendly?
This speech-to-text works well: https://github.com/coqui-ai/STT. openai's "whisper" is probably better but I haven't tried it: https://towardsdatascience.com/transcribe-audio-files-with-openais-whisper-e973ae348aa7
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Introducing Whisper
I use two SST to live-translate audio that I listen to so I can look back (in paragraph form) to see things that I or the youtube has previously said: https://github.com/coqui-ai/STT https://github.com/ratwithacompiler/OBS-captions-plugin
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You can now tether any prod Vector to Wire's Open Source Escape Pod • thedroidyouarelookingfor
I did have to install Coqui STT and go-asticoqui manually before i was able to run Chipper.
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Currently working on a custom Virtual Assistant ('Randy') to help automate things in my shed (mainly CNC equipment) and also perform basic tasks. This morning I was able to get it to publish events on my google calendar.
What do you use as STT? I have heard good things about coqui (https://github.com/coqui-ai/STT) and will use it for my Assistant-build.
- Speech to Text Best Resource
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I put together a tutorial and overview on how to use DeepSpeech to do Speech Recognition in Python
If anyone is looking for a maintained version of DeepSpeech, checkout Coqui's repositories for STT and TTS. Coqui is lead by the engineers that used to work on DeepSpeech at Mozilla.
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CoquiTTS: 🐸💬 - Open Source Text-to-Speech framework.
Link: https://github.com/coqui-ai/STT
- Mozilla Common Voice Adds 16 New Languages and 4,600 New Hours of Speech
Apache Spark
- "xAI will open source Grok"
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Groovy 🎷 Cheat Sheet - 01 Say "Hello" from Groovy
Recently I had to revisit the "JVM languages universe" again. Yes, language(s), plural! Java isn't the only language that uses the JVM. I previously used Scala, which is a JVM language, to use Apache Spark for Data Engineering workloads, but this is for another post 😉.
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🦿🛴Smarcity garbage reporting automation w/ ollama
Consume data into third party software (then let Open Search or Apache Spark or Apache Pinot) for analysis/datascience, GIS systems (so you can put reports on a map) or any ticket management system
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Go concurrency simplified. Part 4: Post office as a data pipeline
also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc.
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Five Apache projects you probably didn't know about
Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features.
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Apache Spark VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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Integrate Pyspark Structured Streaming with confluent-kafka
Apache Spark - https://spark.apache.org/
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Spark – A micro framework for creating web applications in Kotlin and Java
A JVM based framework named "Spark", when https://spark.apache.org exists?
- Rest in Peas: The Unrecognized Death of Speech Recognition (2010)
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PySpark SparkSession Builder with Kubernetes Master
I recently saw a pull request that was merged to the Apache/Spark repository that apparently adds initial Python bindings for PySpark on K8s. I posted a comment to the PR asking a question about how to use spark-on-k8s in a Python Jupyter notebook, and was told to ask my question here.
What are some alternatives?
DeepSpeech - DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
Trino - Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
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)
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
vosk-api - Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
Scalding - A Scala API for Cascading
TTS - :robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
mrjob - Run MapReduce jobs on Hadoop or Amazon Web Services
OBS-captions-plugin - Closed Captioning OBS plugin using Google Speech Recognition
luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.