SpeechVerse: A Large-scale Generalizable Audio Language Model (2405.08295v2)

Abstract: LLMs have shown incredible proficiency in performing tasks that require semantic understanding of natural language instructions. Recently, many works have further expanded this capability to perceive multimodal audio and text inputs, but their capabilities are often limited to specific fine-tuned tasks such as automatic speech recognition and translation. We therefore develop SpeechVerse, a robust multi-task training and curriculum learning framework that combines pre-trained speech and text foundation models via a small set of learnable parameters, while keeping the pre-trained models frozen during training. The models are instruction finetuned using continuous latent representations extracted from the speech foundation model to achieve optimal zero-shot performance on a diverse range of speech processing tasks using natural language instructions. We perform extensive benchmarking that includes comparing our model performance against traditional baselines across several datasets and tasks. Furthermore, we evaluate the model's capability for generalized instruction following by testing on out-of-domain datasets, novel prompts, and unseen tasks. Our empirical experiments reveal that our multi-task SpeechVerse model is even superior to conventional task-specific baselines on 9 out of the 11 tasks.

Understanding LaTeX Instructions for Authors Submitting to *ACL Conferences

When preparing a paper submission for an *ACL conference, adhering to formatting guidelines is crucial. This paper provides detailed instructions for authors using LaTeX, a highly popular document preparation system. Let’s break down its sections and understand its key aspects.

Why These Instructions Matter

For authors looking to submit their work to *ACL conferences, the proper use of LaTeX ensures that their submissions meet mandatory format requirements. This document is a self-conforming LaTeX template with step-by-step instructions making it an excellent reference for authors.

Engine Choice

It’s strongly recommended to use pdfLaTeX to generate PDF files. Other alternatives include:

• XeLaTeX: Particularly suitable for non-Latin scripts.
• LaTeX + dvips + ps2pdf: A less streamlined option compared to pdfLaTeX.

This recommendation simplifies the workflow and ensures compatibility with *ACL’s publication standards.

Setting Up the Document

Here are the essential steps provided for setting up a LaTeX document:

1. Document Class:

   \documentclass[11pt]{article}

2. Loading the Style File:

For the review version:

\usepackage[review]{acl}

For the final version, omit the review option:

\usepackage{acl}

1. Fonts:

Utilize Times Roman for a consistent look:

\usepackage{times}

Alternatives include txfonts or newtx.

Setting Title and Authors

The paper guides setting the title and author section using LaTeX commands:

\title{Your Paper Title} \author{Author Name \and Author Name \and Author Name}

To customize the space allocated for the title and author names box:

\setlength\titlebox{<dim>}

Ensure this is no smaller than 5 cm to meet the document guidelines.

Practical Implications

For intermediate data scientists, understanding how to properly prepare and format a paper for a conference is practically relevant. It reduces the likelihood of submission rejections due to formatting issues. Moreover, properly formatted papers are easier to read and review, conveying professionalism and attention to detail.

Future Considerations

Advancements in tools for document preparation like LaTeX are continuous. Awareness and adoption of best practices and new features can streamline the process further. As AI research evolves, ensuring clarity and standardization in the presentation of research findings will be increasingly critical.

Wrapping Up

This instructional paper provides clear and concise guidelines for using LaTeX to prepare submissions for *ACL conferences. By following these steps, authors can produce well-formatted, professional, and compliant documents, facilitating a smoother review and publication process.