We Claim:

1. A method for enhancing voice search query on a digital platform, the method comprising:

- receiving, by a transceiver [104], an audio query from a user on the digital platform;

- generating, by a processing unit [106], one or more text tokens based on the received audio query;

- sending, by the processing unit[106], the received audio query to a pre-trained first sub-system [108], and the converted text tokens to a pre-trained second sub-system [110];

- identifying, by the pre-trained first sub-system [108], one or more attributes of the user from the received audio query;

- generating, by the pre-trained first sub-system [108], a speaker embedding for the user based on the identified attributes;

- generating, by a second sub-system [110], an enhanced query based on the speaker embedding and the one or more text tokens.

2. The method as claimed in claim 1, wherein the one or more attributes include age, gender, demography, language.

3. The method as claimed in claim 1, wherein the pre-trained first subsystem [108] is trained based on a machine learning model.

4. The method as claimed in claim 1, wherein the pre-trained second subsystem [108] is trained based on a sequence to sequence model.

5. The method as claimed in claim 1, the method further comprising:

- generating search results based on the enhanced query; and

- providing, via a user interface, the generated search results on the digital platform.

6. The method as claimed in claim 1, wherein enhancing is based on a set of historical speaker embeddings and a set of historical vector sequences
associated with the user, stored in a memory unit [114], in an event the voice of the same user is identified by the processing unit[106].

7. A system for enhancing voice search query on a digital platform, the system comprising:

- a transceiver [104] configured to receive an audio query from a user on the digital platform;

- a processing unit [106] configured to:

o generate one or more text tokens based on the received audio query; and

o send the received audio query to a pre-trained first subsystem [108], and the one or more text tokens to a pre-trained second sub-system [110];

wherein,

- the pre-trained first sub-system [108] is configured to:

o identify one or more attributes of the user from the received audio query; and

o generate a speaker embedding for the user based on the identified one or more attributes; and

- the pre-trained second sub-system [110] is configured to:

o generate one or more vector sequences based on the received audio query; and

o generate an enhanced query based on the speaker embedding and the one or more text tokens;

8. The system as claimed in claim 7, wherein the one or more attributes include age, gender, demography, language,....

9. The system as claimed in claim 7, wherein the pre-trained first subsystem [108] is trained based on a machine learning model.

10. The system as claimed in claim 7, wherein the pre-trained second subsystem [108] is trained based on a sequence to sequence model.
11. The system as claimed in claim 7, wherein the processing unit [106] is configured to generate search results based on the enhanced query.

12. The system as claimed in claim 11, the system further comprising a user interface [112] configured to provide the generated search results on the digital platform.

13. The system as claimed in claim 7, wherein enhancing is based on a set of historical speaker embeddings and a set of historical vector sequences associated with the user, stored in a memory unit [114], in an event the voice of the same user is identified by the processing unit[106].