Quality-of-experience measurement for voice services

• US 9,185,005 B2
• Filed: 02/10/2011
• Issued: 11/10/2015
• Est. Priority Date: 02/10/2011
• Status: Expired due to Fees

• Current Assignee: Empire Technology Development LLC (Allied Inventors Management, LLC)
• Original Assignee: Empire Technology Development LLC (Allied Inventors Management, LLC)
• Inventors: Cao, Junwei, Qian, Han, Li, Junwei
• Primary Examiner(s): Liu, Siming
• Application Number:
  US13/641,701
• Publication Number:
  US 20130051271A1
• Time in Patent Office: 1,734 Days
• Field of Search: 370/229, 370/230, 370/235, 370/241, 370/252, 345/156
• US Class Current: 1/1
• CPC Class Codes: G10L 2025/906 Pitch tracking
• CPC Class Codes: G10L 25/09 the extracted parameters being zero crossing rates
• CPC Class Codes: G10L 25/60 for measuring the quality of voice signals
• CPC Class Codes: G10L 25/63 for estimating an emotional state
• CPC Class Codes: G10L 25/90 Pitch determination of speech signals
• CPC Class Codes: H04L 41/5067 Customer-centric QoS measurements
• CPC Class Codes: H04L 43/0852 Delays
• CPC Class Codes: H04L 65/1083 In-session procedures
• CPC Class Codes: H04L 65/80 Responding to QoS

Abstract

Technologies are generally described for determining a quality-of-experience (QoE) of a network communication. In some examples, a process for determining a QoE metric for a network communication includes receiving a media signal from the network communication. The process may also include extracting an experience indicator from the media signal, wherein the experience indicator corresponds to a participant'"'"'s subjective usage experience associated with a service quality of the network communication, and determining the QoE metric for the network communication based on the experience indicator and a quality-of-service (QoS) metric for the network communication.

Claims

1. A method to determine a quality-of-experience (QoE) metric for a network communication involving a participant, comprising:

receiving a media signal from the network communication;

extracting an experience indicator from the media signal, wherein the experience indicator is generated based on the participant'"'"'s subjective experience of a service quality from using the network communication;

evaluating the experience indicator;

after evaluating,

upon a determination that the experience indicator illustrating the service quality of the network communication is subpar, retrieving a quality-of-service (QoS) metric; and

upon a determination that the retrieved QoS metric illustrating the service quality of the network communication is subpar, determining the QoE metric for the network communication based on the evaluated experience indicator and the retrieved QoS metric for the network communication.

2. The method as recited in claim 1, wherein the experience indicator is a voice feature descriptive of the service quality of the network communication.

3. The method as recited in claim 2, wherein the voice feature is an emotion-change amplitude measurement.

4. The method as recited in claim 2, wherein the voice feature is a voice-pacing time measurement.

5. The method as recited in claim 2, wherein the voice feature is a sound-volume pitch measurement.

6. The method as recited in claim 1, wherein the experience indicator is a corpus descriptive of the service quality of the network communication.

7. The method as recited in claim 1, wherein the experience indicator is a facial expression descriptive of the service quality of the network communication.

8. The method as recited in claim 1, wherein the experience indicator is a body gesture descriptive of the service quality of the network communication.

9. A method to determine quality of a network communication involving a participant, comprising:

receiving a media signal from the network communication;

extracting a first corpus from the media signal, wherein the first corpus is generated based on the participant'"'"'s subjective experience of a service quality from using the network communication;

evaluating the first corpus;

after evaluating,

upon a determination that the experience indicator is subpar, retrieving a quality-of-service (QoS) metric; and

upon a determination that the retrieved QoS metric illustrating the service quality of the network communication is subpar, determining a first QoE metric for the network communication based on the evaluated first corpus and the retrieved QoS metric for the network communication.

10. The method as recited in claim 9, wherein the extracting of the corpus from the media signal further comprising:

reducing noise from the received media signal;

extracting a plurality of voice segments from the media signal;

recognizing a plurality of words from the plurality of voice segments; and

identifying the first corpus based on the plurality of words.

11. The method as recited in claim 9, wherein the determining of the first QoE metric further comprising:

retrieving a second QoE metric for a second corpus, wherein the first corpus is subsequent to the second corpus in the media signal; and

initiate the first QoE metric based on the second QoE metric, the first corpus, and the QoS metric for the network communication.

12. The method as recited in claim 9, wherein the determining of the first QoE metric further comprising:

retrieving a second QoE metric for a second corpus, wherein the first corpus is subsequent to the second corpus in the media signal; and

exponentially increasing the first QoE metric based on the second QoE metric, the first corpus, and the QoS metric for the network communication.

13. The method as recited in claim 9, wherein the service quality indicated by the first corpus has a delay condition, a decay condition, or a jitter condition.

14. A non-transitory machine-readable medium having a set of instructions which, in response to execution by a processor, cause the processor to perform a method to determine a quality-of-experience (QoE) metric for a network communication involving a participant, the method comprising:

receiving a media signal from the network communication;

extracting an experience indicator from the media signal, wherein the experience indicator is generated based on the participant'"'"'s subjective experience of a service quality from using the network communication;

evaluating the experience indicator;

after evaluating,

upon a determination that the experience indicator is subpar, retrieving a quality-of-service (QoS) metric; and

upon a determination that the retrieved QoS metric illustrating the service quality of the network communication is subpar, determining the QoE metric for the network communication based on the evaluated experience indicator and the retrieved QoS metric for the network communication.

15. The non-transitory machine-readable medium as recited in claim 14, wherein the experience indicator is a voice feature descriptive of the service quality of the network communication.

16. The non-transitory machine-readable medium as recited in claim 14, wherein the experience indicator is a facial expression descriptive of the service quality of the network communication.

17. The non-transitory machine-readable medium as recited in claim 14, wherein the experience indicator is a corpus descriptive of the service quality of the network communication.