Dorsa Zeinali Email & Phone Number

Boston, Massachusetts, United States

Pittsburgh, Pennsylvania, United States

• Independently learned background on speech recognition through thorough research o Supplemented by Prof. Shinji Watanabe’s course: “Speech Recognition and Understanding”• Learned the ESPnet speech recognition framework and used it to create a speech recognition model for Bengali, which was then added to the toolkit on GitHub •Worked on a project for creating a benchmark and a tool for language-universal alignments, which can also be used for data selection and cleaning o The data available was 2TB of audios and transcriptions from YouTube in 30 different languages o To obtain alignments for this data, trained speech recognition models for 15/30 languages using datasets of varying size o Gained valuable information about using the toolkit, training models using datasets of varying size, and hyperparameter tuning o Learned how to conduct experiments systematically, how to problem-solve when hit with obstacles or bugs, and function as an independent member of a lab that can relied upon o Presented my work at the end of the semester presentations for the lab • Continued work on project started at the JSALT workshop o Trained several models on the synthetic data, and achieved improvement in performance vs training solely on monolingual data o Created different kinds of synthetic data to explore different hypotheses regarding speech quality and performance o Working on creating more variations for further exploration o Independently researched and wrote a paper that was submitted and accepted at a peer-reviewed venue

Baltimore, Maryland, United States

• Participated in a 2-week summer school on speech and language technology • Took the lead on a project which aimed to improve automatic speech recognition on code-switched speech when only monolingual training data is available by generating synthetic code-switched training examples • Researched background in the topic and collaborated with others on the team to come up with a method of generation • Fully implemented the pipeline to efficiently generate audio examples • Learned valuable skills such as thorough literature review, independent problem-solving, and how to approach problems methodically and scientifically • Presented the progress of the project weekly to the rest of workshop and presented the results of the project during the live-broadcasted JSALT 2022 Closing Presentations

Pittsburgh, Pennsylvania, United States

• Created custom machine learning models to predict opioid cravings from wearable data• Created a set of gradient-boosted-tree based classifiers to clean mislabeled data• Identified optimal features from timeseries data using a modified Markov Chain Monte Carlo,accounting temporal dependencies• Increased performance of classifiers by 5-10% using a combination of hyperparameter tuning, data cleaning, and optimal feature selection

Pittsburgh, Pennsylvania, United States

• Using Python, fine-tuned a Factorized-Multimodal-Transformer to classify didactic interactions between parents and children inorder to eventually detect signs of mental illness• Used forced-alignment tools to align audio data and their transcripts• Extracted features from the transcripts in order to feed into the model• Through preparing for the project, obtained valuable knowledge about state of the art Deep Learning methods and models

Chicago, Illinois, United States

• Using Python, manually classified numerous movie reviews into positive and negative for training• First used a Naive-Bayes Classifier on the unlabeled with a given bank of positive and negative words.• Later used a CNN and a RNN to classify the unlabeled data to account for the significance of the order of the words.

Evanston, Illinois, United States

• Visited multiple dermatology practices and photographed images of skin cancers.• Worked with a post-doc on an image recognition program to detect skin cancers based on image data.

Fairfax, Virginia, United States

• Used Autodesk Maya and Matlab to model extraocular muscles in three dimensions.• Worked with a PhD student to develop a model for a biomechanical simulator of strabismus.

Bachelor Of Science - Bs, Computer Science

Activities and Societies: Alpha Chi Omega

High School Diploma

Education record

Doctor Of Philosophy - Phd, Computer Science