CN111951831A - Method for realizing audio quality inspection based on AI - Google Patents
Method for realizing audio quality inspection based on AI Download PDFInfo
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- CN111951831A CN111951831A CN202010860103.0A CN202010860103A CN111951831A CN 111951831 A CN111951831 A CN 111951831A CN 202010860103 A CN202010860103 A CN 202010860103A CN 111951831 A CN111951831 A CN 111951831A
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- 238000007689 inspection Methods 0.000 title claims abstract description 71
- 238000000034 method Methods 0.000 title claims abstract description 25
- 238000012372 quality testing Methods 0.000 claims abstract description 11
- 238000001514 detection method Methods 0.000 claims description 6
- 230000008451 emotion Effects 0.000 claims description 6
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use
- G10L25/51—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use
- G10L25/51—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination
- G10L25/63—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination for estimating an emotional state
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M3/00—Automatic or semi-automatic exchanges
- H04M3/42—Systems providing special services or facilities to subscribers
- H04M3/50—Centralised arrangements for answering calls; Centralised arrangements for recording messages for absent or busy subscribers ; Centralised arrangements for recording messages
- H04M3/51—Centralised call answering arrangements requiring operator intervention, e.g. call or contact centers for telemarketing
- H04M3/5175—Call or contact centers supervision arrangements
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Abstract
The invention discloses a method for realizing audio quality inspection based on AI, comprising the following steps: acquiring a voice file to be subjected to quality inspection; carrying out call split rail on the voice file to be quality tested to obtain a client voice file and a seat voice file; performing ASR recognition on the seat voice file to obtain a seat text file of the seat voice file; the quality inspection engine analyzes each sentence in the seat voice file according to a preset quality inspection rule to obtain an audio information identification result of each sentence, wherein the audio information identification result comprises one or any more of the volume, the speed, whether to mute and whether to scramble in the seat voice file; the quality testing engine analyzes each sentence in the seat text file according to preset quality testing rules to obtain a text information identification result of each sentence, wherein the text information identification result comprises a label of each sentence in the seat text file and the number of times of hitting the rules; and generating an AI quality inspection report of the voice file to be inspected according to the audio information identification result and the text information identification result.
Description
Technical Field
The invention relates to the field of voice communication, in particular to a method for realizing audio quality inspection based on AI.
Background
The customer service quality inspection is to promote enterprise marketing and market development, improve customer satisfaction, perfect customer service and simultaneously evaluate the work of customer service staff. The call center generates huge telephone recordings, quality inspection needs to be carried out on the recordings, whether customer service personnel use standard phrases or not and whether service is in place or not are detected, and the requirements of customers are met. At present, most companies perform quality inspection on audio files such as call recordings and the like by repeatedly listening to manpower to identify audio contents, and then analyze different dimensions such as scoring and cursing the voices, wherein the method is time-consuming, labor-consuming, high in cost, low in pure-manual audio quality inspection efficiency, low in accuracy, large in labor repeatability, and especially under the condition of large business volume, and the workload of manual quality inspection is very large.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide a method for implementing audio quality inspection based on AI, so as to implement AI quality inspection of a voice file.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention provides a method for realizing audio quality inspection based on AI, which comprises the following steps:
acquiring a voice file to be subjected to quality inspection;
carrying out conversation and track splitting on the voice file to be subjected to quality inspection to obtain a client voice file and an agent voice file;
performing ASR recognition on the seat voice file to obtain a seat text file of the seat voice file;
the quality inspection engine analyzes each sentence in the seat voice file according to a preset quality inspection rule to obtain an audio information identification result of each sentence, wherein the audio information identification result comprises one or any more of the volume, the speed, whether to mute and whether to scramble of each sentence in the seat voice file;
the quality inspection engine analyzes each sentence in the agent text file according to a preset quality inspection rule to obtain a text information identification result of each sentence, wherein the text information identification result comprises a label and the number of times of hitting the rule of each sentence in the agent text file;
and generating an AI quality inspection report of the voice file to be inspected according to the audio information identification result and the text information identification result.
In the above scheme, the analyzing, by the quality inspection engine, each sentence in the agent speech file according to a preset quality inspection rule to obtain an audio information recognition result of each sentence further includes:
when the volume of a certain sentence of voice frequency in the seat voice file is larger than a first preset volume, the audio volume of the certain sentence is judged to be too high, and when the volume of the certain sentence of voice frequency in the seat voice file is smaller than a second preset volume, the audio volume of the certain sentence is judged to be too low, wherein the first preset volume is larger than the second preset volume.
In the above scheme, the analyzing, by the quality inspection engine, each sentence in the agent speech file according to a preset quality inspection rule to obtain an audio information recognition result of each sentence further includes:
when the speaking speed of a certain sentence in the seat voice file is larger than a first preset speed, judging that the speaking speed of the sentence is too high, and when the speaking speed of the certain sentence in the seat voice file is smaller than a second preset speed, judging that the speaking speed of the sentence is too low, wherein the first preset speed is larger than the second preset speed.
In the above scheme, the analyzing, by the quality inspection engine, each sentence in the agent speech file according to a preset quality inspection rule to obtain an audio information recognition result of each sentence further includes:
and when the mute time period of a certain sentence in the seat voice file exceeds a first preset time length, judging the sentence as mute.
In the above scheme, the analyzing, by the quality inspection engine, each sentence in the agent speech file according to a preset quality inspection rule to obtain an audio information recognition result of each sentence further includes:
and when the overlapping time of a certain sentence of speech in the seat speech file exceeds a second preset time length, judging the sentence as a speech robbing.
In the above aspect, the method further includes: and carrying out emotion detection on the seat voice file to obtain an emotion detection result.
In the above aspect, the method further includes:
generating the AI score of the voice file to be quality tested according to the text information identification result, wherein the AI score comprises the following steps:
setting a basic score of the voice file to be quality tested;
and according to the number of times of the hit rules of the agent text file, the basic scores are added to obtain the final AI scores.
The invention has the beneficial effects that:
the invention provides a method for realizing audio quality inspection based on AI, which realizes automatic quality inspection of voice files and forms quality inspection reports and AI scores in an AI quality inspection mode, and can reduce the workload of manual quality inspection, reduce the cost of enterprise quality inspection and improve the production efficiency of enterprises.
Drawings
FIG. 1 is a schematic flow chart of a method for implementing audio quality inspection based on AI according to the present invention;
fig. 2 is a schematic flow chart of the AI score for generating a voice file to be quality-tested in the method for implementing audio quality testing based on AI according to the present invention.
Detailed Description
The technical solutions of the present invention are further described in detail below with reference to specific embodiments, and it is obvious that the described embodiments are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
At present, most companies perform quality inspection on audio files such as call recordings and the like by repeatedly listening to manpower to identify audio contents, and then analyze different dimensions such as scoring and cursing of voices, very high cost, low pure-manual audio quality inspection efficiency, low accuracy and large labor repeatability, and especially under the condition of large business volume, the workload of the manpower quality inspection is very large.
In order to perform AI quality inspection on a voice file and improve the quality inspection efficiency of the voice file, the embodiment of the invention provides a method for realizing audio quality inspection based on AI.
The technical solutions provided by the embodiments of the present invention are described in detail below with reference to the accompanying drawings.
An embodiment of the present invention provides a method for implementing audio quality inspection based on AI, as shown in fig. 1, the method includes:
step S101, acquiring a voice file to be subjected to quality inspection;
for step S101, optionally, after the manual seat makes a call, the voice recording file of the call is stored in the database, and after the quality inspection task is created, the voice recording file of the call is acquired for quality inspection.
Step S102, carrying out conversation and track splitting on the voice file to be subjected to quality inspection to obtain a client voice file and an agent voice file;
step S103, carrying out ASR recognition on the seat voice file to obtain a seat text file of the seat voice file;
step S104, the quality inspection engine analyzes each sentence in the seat voice file according to a preset quality inspection rule to obtain an audio information identification result of each sentence;
the audio information identification result comprises one or more of the volume, the speed, the silence and the robbing of words of each sentence in the agent voice file.
Step S105, the quality inspection engine analyzes each sentence in the seat text file according to a preset quality inspection rule to obtain a text information identification result of each sentence;
and the text information identification result comprises a label of each sentence in the agent text file and the number of times of the hit rule.
And step S106, generating an AI quality inspection report of the voice file to be inspected according to the audio information identification result and the text information identification result.
In one example, the analyzing, by the quality inspection engine, each sentence in the agent voice file according to a preset quality inspection rule to obtain an audio information recognition result of each sentence further includes:
when the volume of a certain sentence of voice frequency in the seat voice file is larger than a first preset volume, the audio volume of the certain sentence is judged to be too high, and when the volume of the certain sentence of voice frequency in the seat voice file is smaller than a second preset volume, the audio volume of the certain sentence is judged to be too low, wherein the first preset volume is larger than the second preset volume.
Optionally, the first preset volume is 50 db, and the second preset volume is 30 db.
In one example, the analyzing, by the quality inspection engine, each sentence in the agent voice file according to a preset quality inspection rule to obtain an audio information recognition result of each sentence further includes:
when the speaking speed of a certain sentence in the seat voice file is larger than a first preset speed, judging that the speaking speed of the sentence is too high, and when the speaking speed of the certain sentence in the seat voice file is smaller than a second preset speed, judging that the speaking speed of the sentence is too low, wherein the first preset speed is larger than the second preset speed.
Optionally, the first preset speech rate is 6 words/second, and the second preset speech rate is 2 words/second.
In one example, the analyzing, by the quality inspection engine, each sentence in the agent voice file according to a preset quality inspection rule to obtain an audio information recognition result of each sentence further includes:
and when the mute time period of a certain sentence in the seat voice file exceeds a first preset time length, judging the sentence as mute.
Optionally, the first preset time period is 3 seconds.
In one example, the analyzing, by the quality inspection engine, each sentence in the agent voice file according to a preset quality inspection rule to obtain an audio information recognition result of each sentence further includes:
and when the overlapping time of a certain sentence of speech in the seat speech file exceeds a second preset time length, judging the sentence as a speech robbing.
Optionally, the second preset time period is 2 seconds.
In one example, the method further comprises: and carrying out emotion detection on the seat voice file to obtain an emotion detection result.
In an example, the embodiment of the present invention further includes generating an AI score of the voice file to be quality-tested according to the text information recognition result, as shown in fig. 2, where the AI score includes:
step S201, setting a basic score of the voice file to be subjected to quality inspection;
and step S202, according to the number of times of the hit rules of the agent text file, the basic scores are added to obtain the final AI scores.
For step S202, optionally, when there is a sentence hit rule in the seat text file, 1 point is added to the basic score, the seat text file is traversed, and the total number of times of hit rules is calculated to obtain a final AI score.
The embodiments of the present invention have been described above with reference to the accompanying drawings, but the present invention is not limited to the above-described embodiments, which are merely illustrative and not restrictive; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, which are within the protection scope of the present invention.
Claims (7)
1. A method for realizing audio quality inspection based on AI is characterized by comprising the following steps:
acquiring a voice file to be subjected to quality inspection;
carrying out conversation and track splitting on the voice file to be subjected to quality inspection to obtain a client voice file and an agent voice file;
performing ASR recognition on the seat voice file to obtain a seat text file of the seat voice file;
the quality inspection engine analyzes each sentence in the seat voice file according to a preset quality inspection rule to obtain an audio information identification result of each sentence, wherein the audio information identification result comprises one or any more of the volume, the speed, whether to mute and whether to scramble of each sentence in the seat voice file;
the quality inspection engine analyzes each sentence in the agent text file according to a preset quality inspection rule to obtain a text information identification result of each sentence, wherein the text information identification result comprises a label and the number of times of hitting the rule of each sentence in the agent text file;
and generating an AI quality inspection report of the voice file to be inspected according to the audio information identification result and the text information identification result.
2. The AI-based method according to claim 1, wherein the analyzing, by the quality testing engine, each sentence in the agent voice file according to the preset quality testing rules to obtain the audio information recognition result of each sentence further comprises:
when the volume of a certain sentence of voice frequency in the seat voice file is larger than a first preset volume, the audio volume of the certain sentence is judged to be too high, and when the volume of the certain sentence of voice frequency in the seat voice file is smaller than a second preset volume, the audio volume of the certain sentence is judged to be too low, wherein the first preset volume is larger than the second preset volume.
3. The AI-based method according to claim 1, wherein the analyzing, by the quality testing engine, each sentence in the agent voice file according to the preset quality testing rules to obtain the audio information recognition result of each sentence further comprises:
when the speaking speed of a certain sentence in the seat voice file is larger than a first preset speed, judging that the speaking speed of the sentence is too high, and when the speaking speed of the certain sentence in the seat voice file is smaller than a second preset speed, judging that the speaking speed of the sentence is too low, wherein the first preset speed is larger than the second preset speed.
4. The AI-based method according to claim 1, wherein the analyzing, by the quality testing engine, each sentence in the agent voice file according to the preset quality testing rules to obtain the audio information recognition result of each sentence further comprises:
and when the mute time period of a certain sentence in the seat voice file exceeds a first preset time length, judging the sentence as mute.
5. The AI-based method according to claim 1, wherein the analyzing, by the quality testing engine, each sentence in the agent voice file according to the preset quality testing rules to obtain the audio information recognition result of each sentence further comprises:
and when the overlapping time of a certain sentence of speech in the seat speech file exceeds a second preset time length, judging the sentence as a speech robbing.
6. The AI-based method of claim 1, wherein the AI-based method further comprises: and carrying out emotion detection on the seat voice file to obtain an emotion detection result.
7. The AI-based method of claim 1, wherein the AI-based method further comprises:
generating the AI score of the voice file to be quality tested according to the text information identification result, wherein the AI score comprises the following steps:
setting a basic score of the voice file to be quality tested;
and according to the number of times of the hit rules of the agent text file, the basic scores are added to obtain the final AI scores.
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112511698A (en) * | 2020-12-03 | 2021-03-16 | 普强时代(珠海横琴)信息技术有限公司 | Real-time call analysis method based on universal boundary detection |
| CN112885376A (en) * | 2021-01-23 | 2021-06-01 | 深圳通联金融网络科技服务有限公司 | Method and device for improving voice call quality inspection effect |
| CN113177114A (en) * | 2021-05-28 | 2021-07-27 | 重庆电子工程职业学院 | Natural language semantic understanding method based on deep learning |
| CN113411454A (en) * | 2021-06-17 | 2021-09-17 | 商客通尚景科技（上海）股份有限公司 | Intelligent quality inspection method for real-time call voice analysis |
| CN113506585A (en) * | 2021-09-09 | 2021-10-15 | 深圳市一号互联科技有限公司 | Quality evaluation method and system for voice call |
| CN113689862A (en) * | 2021-08-23 | 2021-11-23 | 南京优飞保科信息技术有限公司 | Quality inspection method and system for customer service seat voice data |
| CN113808574A (en) * | 2021-10-28 | 2021-12-17 | 平安消费金融有限公司 | AI voice quality inspection method, device, equipment and storage medium based on voice information |
| CN114006986A (en) * | 2021-10-29 | 2022-02-01 | 平安普惠企业管理有限公司 | Outbound call compliance early warning method, device, equipment and storage medium |
| CN114842849A (en) * | 2022-04-24 | 2022-08-02 | 马上消费金融股份有限公司 | Voice conversation detection method and device |
| CN115118818A (en) * | 2022-06-27 | 2022-09-27 | 平安银行股份有限公司 | Quality inspection method and device for call recording data, electronic equipment and storage medium |
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| CN113808574A (en) * | 2021-10-28 | 2021-12-17 | 平安消费金融有限公司 | AI voice quality inspection method, device, equipment and storage medium based on voice information |
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| CN115118818A (en) * | 2022-06-27 | 2022-09-27 | 平安银行股份有限公司 | Quality inspection method and device for call recording data, electronic equipment and storage medium |
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