Dubverse Black

Dubverse Black is a newsletter focused on the latest advancements in technology, particularly in AI and machine learning. It covers topics like text-to-speech, speech-to-text technologies, AI-driven translation, ChatGPT applications, self-supervised learning, voice cloning, and the inclusivity of non-English languages in AI. The newsletter emphasizes on the development and application of generative AI and Large Language Models (LLMs) in improving communication and content accessibility.

Artificial Intelligence Machine Learning Text-to-Speech Technology Speech-to-Text Technology Language Translation Voice Cloning Generative AI Inclusivity in Technology

The hottest Substack posts of Dubverse Black

And their main takeaways

A State-of-the-Art Survey of Text-to-Speech Technology 2023

157 implied HN points • 24 Oct 23
🕹 Technology AI Generative AI Text-to-Speech Deep Learning
  1. The latest innovation in Generative AI focuses on Speech Models that can produce human-like voices, even in songs.
  2. Self-Supervised Learning is revolutionizing Text-to-Speech technology by allowing models to learn from unlabelled data for better quality outcomes.
  3. Text-to-Speech systems are structured in three main parts, utilizing models like TORTOISE and BARK to produce expressive and high-quality audio.

Running RVC Models on the Easy GUI

78 implied HN points • 13 Oct 23
🕹 Technology AI Machine Learning Data processing
  1. Retrieval-based Voice Conversion (RVC) uses a deep neural network to transform one voice into another.
  2. RVC models are fast, allow voice cloning, are budget-friendly, and work well with minimal speech.
  3. To run RVC models on Google Colab, connect to a custom GCE runtime, follow specific steps to process data, and train the models.

Whisper's Word-Level Timestamps are Out

117 implied HN points • 26 Jul 23
🕹 Technology AI Technology
  1. Whisper's Word-Level Timestamps have been introduced for enhanced accuracy.
  2. Word-Level Timestamps offer benefits like video accessibility, SEO optimization, and content monetization.
  3. Consider using transcription over translation for accurate alignment with word-level timestamps.

Evals are all we need

58 implied HN points • 26 Oct 23
🕹 Technology AI Voice Cloning Deep Learning
  1. Evaluations are crucial for advancing voice cloning technology
  2. Open-source community is making strides in developing Large Language Models
  3. Mean Opinion Score (MOS) and proposed evals like Speaker Similarity and Intelligibility are important for evaluating voice cloning technology

Case for Foundation Models beyond English

117 implied HN points • 18 Jul 23
🕹 Technology Tokenization Cost Analysis
  1. The dominance of English in technology can limit inclusivity in AI models
  2. Processing non-English languages in AI can be more costly due to tokenization concepts like fertility
  3. Efforts are being made to enhance representation of non-English languages in AI, promoting diversity and inclusivity
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Self Supervised Learning (SSL)

98 implied HN points • 09 Aug 23
🕹 Technology AI/ML Research Papers
  1. Self Supervised Learning (SSL) is a way to train models using synthetic labels generated from the data itself.
  2. SSL can be applied in different domains like NLP, Speech, Vision using techniques like MLM, LM, VicReg, Autoencoders, and VAE.
  3. SSL enables models to learn powerful data representations inexpensively which can be utilized for various tasks like transfer learning and fine-tuning.

Improving Indic Text to Speech using ChatGPT

176 implied HN points • 25 Jan 23
  1. Improving pronunciation with ChatGPT for text-to-speech projects
  2. Using Few Shot Learning on GPT3 to recognize patterns
  3. Utilizing Hindi in ChatGPT for English pronunciation assistance

Can I hack OpenAI's ChatGPT Detector?

137 implied HN points • 08 Feb 23
  1. Prompt Injection can manipulate AI models like GPT to follow specific instructions.
  2. By using prompt injection, it's possible to replicate GPT-like applications and influence model responses.
  3. LLMs can not only generate text but also classify information, and prompt injection can impact classifier outputs.

Can we do better than ChatGPT for translation?

98 implied HN points • 05 Jul 23
🕹 Technology Language Models Open Source
  1. The ChatGPT-powered translations are still performing better than other models for most translations.
  2. COMET is an important metric for evaluating translations, focusing on fluency, adequacy, and meaning conveyed.
  3. Open source LLMs like IndicTrans2 and NLLB may be inferior to GCP and GPT, but they can be fine-tuned for better performance.

When Whisper 1.0 Gets It Wrong: An Inside Look at Speech-to-Text Failures

117 implied HN points • 19 Apr 23
🕹 Technology AI Speech Recognition Data Collection
  1. OpenAI's Whisper model, while impressive, still has limitations and failures in speech-to-text accuracy.
  2. Whisper's challenges include repeating segments, mixing voice and non-voice activities, and inaccuracies in timestamps.
  3. The drawbacks of Whisper 1.0 present opportunities for learning, adaptation, and further development in enhancing speech-to-text technology.

What's cooking (Q2'23 edition)

58 implied HN points • 03 May 23
🕹 Technology AI Communication Language
  1. Generative AI technology is advancing rapidly and impacting the development of products.
  2. Dubverse tools focus on converting communication artifacts across languages using various modalities.
  3. Challenges in language translation can be addressed through emerging Generative AI techniques.