优酷算法工程师-语音算法
校招全职虎鲸文娱2026届秋季应届生招聘地点：杭州状态：招聘
任职要求
1、在语音合成、情绪迁移、音频检索、音频分类、声纹识别、语音增强等方面有相关的项目经验，并能够对其中某一领域的算法深入研发并努力创新 2、熟悉传统机器学习基础理论，熟悉深度学习开源框架，深入理解DNN/RNN/CNN/lstm原理,掌握至少一个深度学习…
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工作职责
应用声纹识别、语音合成、情绪迁移等音频技术处理阿里大文娱集团海量音频数据，紧跟业界前沿技术方向，在真实的语音场景进行落地应用，实现音色适配、情绪饱满、高自然度拟人的音频合成，期待追求卓越、自我驱动、聪明乐观的优秀人士加入阿里大文娱集团，共同开创影视工业化的商业新格局 具体职责包括但不限于： 1、负责基于海量数据和复杂业务场景，和团队其他成员一起构建面向多语言多说话人多情绪的一流语音合成系统 2、负责语音合成相关算法设计，包括Emotional TTS、Speaker Recognition、Instant Voice Clone等模块的算法优化和在实际场景上的落地 3、跟踪业界前沿技术和方法，持续探索语音合成技术的新能力和新应用，解决资源受限场景的实际问题，持续提升语音合成核心能力
包括英文材料
算法+
https://roadmap.sh/datastructures-and-algorithms
Step by step guide to learn Data Structures and Algorithms in 2025
https://www.hellointerview.com/learn/code
A visual guide to the most important patterns and approaches for the coding interview.
https://www.w3schools.com/dsa/
机器学习+
https://www.youtube.com/watch?v=0oyDqO8PjIg
Learn about machine learning and AI with this comprehensive 11-hour course from @LunarTech_ai.
https://www.youtube.com/watch?v=i_LwzRVP7bg
Learn Machine Learning in a way that is accessible to absolute beginners.
https://www.youtube.com/watch?v=NWONeJKn6kc
Learn the theory and practical application of machine learning concepts in this comprehensive course for beginners.
https://www.youtube.com/watch?v=PcbuKRNtCUc
Learn about all the most important concepts and terms related to machine learning and AI.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
RNN+
https://d2l.ai/chapter_recurrent-neural-networks/rnn.html
A neural network that uses recurrent computation for hidden states is called a recurrent neural network (RNN).
https://www.deeplearningbook.org/contents/rnn.html
Recurrent neural networks, or RNNs (Rumelhart et al., 1986a), are a family of neural networks for processing sequential data.
https://www.ibm.com/think/topics/recurrent-neural-networks
A recurrent neural network or RNN is a deep neural network trained on sequential or time series data to create a machine learning (ML) model that can make sequential predictions or conclusions based on sequential inputs.
CNN+
https://learnopencv.com/understanding-convolutional-neural-networks-cnn/
Convolutional Neural Network (CNN) forms the basis of computer vision and image processing.
[英文] CNN Explainer
https://poloclub.github.io/cnn-explainer/
Learn Convolutional Neural Network (CNN) in your browser!
https://www.deeplearningbook.org/contents/convnets.html
Convolutional networks(LeCun, 1989), also known as convolutional neuralnetworks, or CNNs, are a specialized kind of neural network for processing data.
https://www.youtube.com/watch?v=2xqkSUhmmXU
MIT Introduction to Deep Learning 6.S191: Lecture 3 Convolutional Neural Networks for Computer Vision
LSTM+
https://colah.github.io/posts/2015-08-Understanding-LSTMs/
Humans don’t start their thinking from scratch every second.
https://d2l.ai/chapter_recurrent-modern/lstm.html
The term “long short-term memory” comes from the following intuition.
https://developer.nvidia.com/discover/lstm
A Long short-term memory (LSTM) is a type of Recurrent Neural Network specially designed to prevent the neural network output for a given input from either decaying or exploding as it cycles through the feedback loops.
https://www.youtube.com/watch?v=YCzL96nL7j0
Basic recurrent neural networks are great, because they can handle different amounts of sequential data, but even relatively small sequences of data can make them difficult to train.
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