Method and system for automatically visualizing a transcript

1 . A method for automatically visualizing a transcript, the method comprising:

receiving, by at least one processor, a voice input from at least one entity;

recognizing, by the at least one processor, speech from the voice input in response to detecting a predetermined keyword or phrase in the voice input, the predetermined keyword or phrase representing a wake word for which transcription of the voice input shall commence;

removing, by the at least one processor, unwanted noise from the recognized speech using at least one signal processing technique to enhance the speech, wherein the speech is processed to remove an unwanted noise, wherein the at least one signal processing technique includes a bandpass filter, a low-pass filter, loudness control, and/or acoustic echo cancellation;

converting, by the at least one processor, the enhanced speech into a transcript using a speech transcription technique; and

automatically visualizing, by the at least one processor, the transcript into a design diagram, comprising:

training a language model for aligning specific parts of images with text to create a frozen language model;

converting the transcript into tokenized text;

passing the tokenized text into a frozen language model to convert the tokenized text into a sequence of embeddings that captures meaning and context of the tokenized text;

mapping, by an embedding layer, the tokenized text to vector representations;

processing, by one or more hidden layers, the vector representations using a transformer architecture or other neural network architecture to generate transformed representations; and

generating, by an output layer from the transformed representations, an output including text predictions, scores, and/or embeddings.

2 . The method of claim 1 , wherein the design diagram is a flowchart.

3 . The method as claimed in claim 1 , wherein the speech transcription technique comprises at least one from among a natural language understanding technique and a natural language generation technique.

4 . The method as claimed in claim 1 , wherein the automatically visualizing the transcript into the design diagram comprises:

generating, by the at least one processor, the design diagram using a frozen clip model.

5 . The method as claimed in claim 1 , wherein the voice input is received via an audio input device.

6 . The method as claimed in claim 1 , wherein the at least one entity is one from among a team member involved in a project, a team lead of the project, a project reviewer, a user to present the project, and a client.

7 . A computing device for automatically visualizing a transcript, the computing device comprising:

a processor;

a memory; and

a communication interface coupled to each of the processor and the memory,

wherein the processor is configured to:

receive a voice input from at least one entity;

recognize speech from the voice input in response to detecting a predetermined keyword or phrase in the voice input, the predetermined keyword or phrase representing a wake word for which transcription of the voice input shall commence;

remove unwanted noise from the recognized speech using at least one signal processing technique to enhance the speech, wherein the speech is processed to remove an unwanted noise, wherein the at least one signal processing technique includes a bandpass filter, a low-pass filter, loudness control, and/or acoustic echo cancellation;

convert the enhanced speech into a transcript using a speech transcription technique; and

automatically visualize the transcript into a design diagram, comprising:

train a language model for aligning specific parts of images with text to create a frozen language model;

convert the transcript into tokenized text;

pass the tokenized text into a frozen language model to convert the tokenized text into a sequence of embeddings that captures meaning and context of the tokenized text;

map, by an embedding layer, the tokenized text to vector representations;

process, by one or more hidden layers, the vector representations using a transformer architecture or other neural network architecture to generate transformed representations; and

generate, by an output layer from the transformed representations, an output including text predictions, scores, and/or embeddings.

8 . The computing device of claim 7 , wherein the design diagram is a flowchart.

9 . The computing device as claimed in claim 7 , wherein the speech transcription technique comprises at least one from among a natural language understanding technique and a natural language generation technique.

10 . The computing device as claimed in claim 7 , wherein to automatically visualize the transcript into the design diagram, the processor is further configured to:

generate the design diagram using a frozen clip model.

11 . The computing device as claimed in claim 7 , wherein the voice input is received via an audio input device.

12 . A non-transitory computer readable storage medium storing instructions for automatically visualizing a transcript, the storage medium comprising executable code which, when executed by a processor, causes the processor to perform operations comprising:

receive a voice input from at least one entity;

recognize speech from the voice input in response to detecting a predetermined keyword or phrase in the voice input, the predetermined keyword or phrase representing a wake word for which transcription of the voice input shall commence;

remove unwanted noise from the recognized speech using at least one signal processing technique to enhance the speech, wherein the speech is processed to remove an unwanted noise, wherein the at least one signal processing technique includes a bandpass filter, a low-pass filter, loudness control, and/or acoustic echo cancellation;

convert the enhanced speech into a transcript using a speech transcription technique; and

automatically visualize the transcript into a design diagram, comprising:

train a language model for aligning specific parts of images with text to create a frozen language model;

convert the transcript into tokenized text;

pass the tokenized text into frozen language model to convert the tokenized text into a sequence of embeddings that captures meaning and context of the tokenized text;

map, by an embedding layer, the tokenized text to vector representations;

process, by one or more hidden layers, the vector representations using a transformer architecture or other neural network architecture to generate transformed representations; and

generate, by an output layer from the transformed representations, an output including text predictions, scores, and/or embeddings.

13 . The storage medium of claim 12 , wherein the design diagram is a flowchart.

14 . The storage medium as claimed in claim 12 , wherein the speech transcription technique comprises at least one from among a natural language understanding technique and a natural language generation technique.

15 . The storage medium as claimed in claim 12 , wherein to automatically visualize the transcript into the design diagram, when executed by the processor, the executable code further causes the processor to:

generate the design diagram using a frozen clip model.

16 . The storage medium as claimed in claim 12 , wherein the voice input is received via an audio input device.