Real Time Speech Based Integrated Development Environment for C Program

This Automatic Speech Recognition (ASR) is the process which converts an acoustic signal captured by the microphone to written text. The motivation of the paper is to create a speech based Integrated Development Environment (IDE) for C program. This paper proposes a technique to facilitate the visually impaired people or the person with arm injuries with excellent programming skills that can code the C program through voice input. The proposed system accepts the C program as voice input and produces compiled C program as output. The user should utter each line of the C program through voice input. First the voice input is recognized as text. The recognized text will be converted into C program by using syntactic constructs of the C language. After conversion, C program will be fetched as input to the IDE. Furthermore, the IDE commands like open, save, close, compile, run are also given through voice input only. If any error occurs during the compilation process, the error is corrected through voice input only. The errors can be corrected by specifying the line number through voice input. Performance of the speech recognition system is analyzed by varying the vocabulary size as well as number of mixture components in HMM.

Ask Me Any Type:Type Inference Plugin for Partial Code on the Web and in the Integrated Development Environment

Inferring the fully qualified names(FQNs)of undeclared receiving objects and non-fully-qualified type names(non-FQNs)in partial code is critical for effectively searching,understanding,and reusing partial code.Existing type inference tools,such as COSTER and SNR,rely on a symbolic knowledge base and adopt a dictionary-lookup strategy to map simple names of undeclared receiving objects and non-FQNs to FQNs.However,building a symbolic knowledge base requires parsing compilable code files,which limits the collection of APIs and code contexts,resulting in out-of-vocabulary(OOV)failures.To overcome the limitations of a symbolic knowledge base for FQN inference,we implemented Ask Me Any Type(AMAT),a type of inference plugin embedded in web browsers and integrated development environment(IDE).Unlike the dictionary-lookup strategy,AMAT uses a cloze-style fill-in-the-blank strategy for type inference.By treating code as text,AMAT leverages a fine-tuned large language model(LLM)as a neural knowledge base,thereby preventing the need for code compilation.Experimental results show that AMAT outperforms state-of-the-art tools such as COSTER and SNR.In practice,developers can directly reuse partial code by inferring the FQNs of unresolved type names in real time.

IRP/DSM and Sustainable Development

This paper introduces the energy consumption status in China, elaborate the affects of the unreasonable energy consumption structure on energy environment and sustainable development of economy. Simultaneously, it points out the solution, i.e., to implement integrated resources planning (IRP)/demand side management (DSM), and gives some recommendations on the way of implementing IRP/DSM.