1. A method of security negotiation for idle state mobility from a first network to a long term evolution (LTE) network using a mobility management entity (MME), the method comprising:
receiving an authentication vector-related key from a service general packet radio service (GPRS) support node (SGSN) in the first network;
receiving security capabilities of a user equipment (UE) including non-access stratum (NAS) security capabilities of the UE from the UE;
selecting a NAS security algorithm supported by the NAS security capabilities of the UE;
sending a message that indicates the selected NAS security algorithm to the UE; and
deriving a NAS protection key with the selected NAS security algorithm from the authentication vector-related key.
2. The method of claim 1, wherein the security capabilities is received in a tracking area update (TAU) request message.
3. The method of claim 1, wherein the message that indicates the selected NAS security algorithm is a NAS security mode command message.
4. The method of claim 1, wherein the message that indicates the selected NAS security algorithm is a tracking area update (TAU) accept message.
5. The method of claim 1, further comprising, before the sending the message that indicates the selected NAS security algorithm:
protecting the message that indicates the selected NAS security algorithm, with the derived NAS protection key.
6. The method of claim 1, wherein the first network is one of a second generation (2G) network, a third generation (3G) network and a second LTE network.
7. The method of claim 1, wherein the first network is a second generation (2G) network and the authentication vector-related key includes an encryption key (Kc).
8. The method of claim 1, wherein the first network is a third generation (3G) network and the authentication vector-related key includes an integrity key (IK) and an encryption key (CK).
9. The method of claim 1, wherein the authentication vector-related key is received in a context response message.
10. The method of claim 2, wherein the authentication vector-related key is received in a context response message and the message that indicates the selected NAS security algorithm is a NAS security mode command message.
11. A mobility management entity (MME) performing security negotiation for idle state mobility from a first network to a long term evolution (LTE) network, comprising:
a receiver that receives from a user equipment (UE) security capabilities of the UE including non-access stratum (NAS) security capabilities of the UE, wherein the receiver further receives an authentication vector-related key from a service general packet radio service (GPRS) support node (SGSN) in the first network;
a processor that selects a NAS security algorithm supported by the NAS security capabilities of the UE, and derives a NAS protection key with the selected NAS security algorithm from the authentication vector-related key; and
a transmitter that sends a message that indicates the selected NAS security algorithm to the UE.
12. The MME of claim 11, wherein the receiver receives the security capabilities through a tracking area update (TAU) request message.
13. The MME of claim 11, wherein the message that indicates the selected NAS security algorithm is a NAS security mode command message.
14. The MME of claim 11, wherein the message that indicates the selected NAS security algorithm is a tracking area update (TAU) accept message.
15. The MME of claim 11, wherein the processor further protects the message that indicates the selected NAS security algorithm with the derived NAS protection key.
16. The MME of claim 11, wherein the first network is one of a second generation (2G) network, a third generation (3G) network, and a second LTE network.
17. The MME of claim 11, wherein the first network is a second generation (2G) network and the authentication vector-related key includes an encryption key (Kc).
18. The MME of claim 11, wherein the first network is a third generation (3G) network and the authentication vector-related key includes an integrity key (IK) and an encryption key (CK).
19. The MME of claim 11, wherein the authentication vector-related key is received in a context response message.
20. The MME of claim 12, wherein the authentication vector-related key is received in a context response message and the message that indicates the selected NAS security algorithm is a NAS security mode command message.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. Method for recognizing speech,
wherein at least keywords (Kj) in a received speech phrase (SP) are recognized employing a keyword spotting based recognition process (12) and a given language model (LM),
wherein a combination of at least one first language or keyword model (KM) containing andor describing possible in-vocabulary or keywords or phrases (Kj) and one second language or out-of-vocabulary model (OOVM) describing at least in part out-of-vocabulary words or phrases (Gj) is used as said language model (LM), and
wherein a global penalty (Pglob) is associated to andor introduced or inserted into said language model (LM) so as to increase the recognition of keywords (Kj), characterized in that
at least one variable penalty value (Ptrans, P1, . . . , P6) is associated with andor used to define the global penalty (Pglob).
2. Method according to claim 1,
wherein said variable penalty value (Ptrans, P1, . . . , P6) is in each case made dependent on or a function of the recognition process, of an user input, of a received speech phrase (SP) per se andor their characteristics or the like.
3. Method according to anyone of the preceding claims,
wherein at least one statistical model, garbage model (GM) andor the like is used as said out-of-vocabulary model (OOVM).
4. Method according to anyone of the preceding claims,
wherein said out-of-vocabulary model (OOVM) and in particular said garbage model (GM) is chosen to contain at least a phone* grammar or the like.
5. Method according to anyone of the preceding claims,
wherein said variable penalty value (Ptrans, P1, . . . , P6) is associated with a transition (T) of the recognition process (12), in particular from a keyword model (KM) to an out-of-vocabulary model (OOVM).
6. Method according to anyone of the preceding claims,
wherein said variable penalty value (Ptrans, P1, . . . , P6) isin particular in each caseassociated with a recognition step andor recognition or processing time of said recognition process (12) within said out-of-vocabulary model (OOVM) or a garbage model (GM).
7. Method according to anyone of the preceding claims,
wherein a lattice structure of recognition paths or the like is used in said keyword model (KM) andor said out-of-vocabulary (OOVM) or garbage model (GM).
8. Method according to claim 7,
wherein with at least a part of said recognition paths in said out-of-vocabulary (OOVM) is associated a variable penalty value (Ptrans, P1, . . . , P6), in particular within the statistical information of said out-of-vocabulary model (OOVM) or garbage model (GM).
9. Method according to any of the preceding claims,
wherein a Markov model, and in particular a single state Markov model, is at least contained in said out-of-vocabulary model (OOVM) or garbage model (GM), and
wherein a variable penalty value (P1, . . . P6) is associated with self-transitions of the recognition process within said Markov model.
10. Method according to anyone of the preceding claims,
wherein a variable penalty value is associated with all transitions in a Markov model.
11. Method according to anyone of the preceding claims,
wherein said variable penalty value (Ptrans, P1, . . . , P6) is made dependent on the particular application, the application status andor on user preferences.
12. Method according to anyone of the preceding claims,
wherein said variable penalty value (Ptrans, P1, . . . , P6) is varied interactively, in particular by an user action via an user interface.
13. Method according to anyone of the preceding claims,
wherein said variable penalty value (Ptrans, P1, . . . , P6) is hold and stored in a randomly accessible manner in particular within the model statistical information of the language model (LM).
14. Method according to anyone of the preceding claims,
wherein likelihoods (LKM, LGM), global scores or the like for recognition results in said keyword model (KM) and in said out-of-vocabulary model (OOVM)
in particular said garbage model (GM)are determined, the latter of which being variably penalized, and
wherein a recognition result (RSP) is accepted with the keyword model likelihood (LKM) being larger than a respective out-of-vocabulary model likelihood (LGM), and is rejected as being out of vocabulary otherwise.